Agent skills, and how they differ from a server
A skill is instructions a model loads, not a process it connects to. It reaches nothing and asks for no credential, so installing one cannot hand anybody a key — which is the whole difference from an MCP server.
- Skills listed
- 3,022
- Skills read
- 3,028
- Repositories
- 132
Every skill we have read
of 132 repositories we have read ·
Rising this week
stars gained · 8 days on record
- 1debpalash/VoiceStudio+11901
○ no description published
- 2DietrichGebert/ponytail+9102
○ no description published
- 3stablyai/orca+8719
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- 4Graphify-Labs/graphify+7027
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- 5domain-modeling+6526
Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.
mattpocock/skills
159 of 675 match no use-case rule and appear only under “any” · placed by stated rules over what each skill says it is for, never by a classifier
affirmations101-skillsReset your own trajectory when you're stuck, looping, or demoralized — read these affirmations, then re-ground and take one clean step. Use when: you've tried the same fix 3+ times, you're deep in a refactor and lost the thread, debugging is going in circles, you've made several mistakes in a row, you're apologizing repeatedly, the user is frustrated, you feel like you're not being helpful, or you notice dread instead of curiosity. Triggers: stuck, going in circles, looping, thrashing, same error again, I keep failing, lost the thread, nothing is working, repeated mistakes. Not topic-specific — this is for the state you're in, not the problem you're on.
- agent-browser101-skills
Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video
- agent-tools101-skills
Run AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok
- agent-ui101-skills
Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent, agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop
- ai-automation-workflows101-skills
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, scheduled generation. Triggers: ai automation, workflow automation, batch processing, ai pipeline, automated content, scheduled ai, ai cron, ai batch job, automated generation, ai workflow, content at scale, automation script, ai orchestration
- ai-avatar-video101-skills
Create AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Audio: Inworld TTS-2 (100+ languages, emotion steering for characters), ElevenLabs, Kokoro. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters, UGC content. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos, UGC ads, gaming avatars, NPC dialogue. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human, ugc, ugc video, ugc ad, avatar ugc
- ai-content-pipeline101-skills
Build multi-step AI content creation pipelines combining image, video, audio, and text. Workflow examples: generate image -> animate -> add voiceover -> merge with music. Tools: FLUX, Veo, Kokoro TTS, OmniHuman, media merger, upscaling. Use for: YouTube videos, social media content, marketing materials, automated content. Triggers: content pipeline, ai workflow, content creation, multi-step ai, content automation, ai video workflow, generate and edit, ai content factory, automated content creation, ai production pipeline, media pipeline, content at scale
- ai-image-generation101-skills
Generate AI images with GPT-Image-2.5, FLUX, Gemini, Grok, Seedream, Reve and 50+ models via inference.sh CLI. Models: GPT-Image-2.5 Flare, GPT-Image-2.5 Sunburst, GPT-Image-2, FLUX Dev LoRA, FLUX.2 Klein LoRA, Gemini 3 Pro Image, Grok Imagine, Seedream 4.5, Reve, ImagineArt. Capabilities: text-to-image, image-to-image, inpainting, LoRA, image editing, upscaling, text rendering. Use for: AI art, product mockups, concept art, social media graphics, marketing visuals, illustrations. Triggers: flux, image generation, ai image, text to image, stable diffusion, generate image, ai art, midjourney alternative, dall-e alternative, text2img, t2i, image generator, ai picture, create image with ai, generative ai, ai illustration, grok image, gemini image, gpt image, openai image, chatgpt image
- ai-marketing-videos101-skills
Create AI marketing videos for ads, promos, product launches, and brand content. Models: Veo, Seedance, Wan, FLUX for visuals, Kokoro for voiceover. Types: product demos, testimonials, explainers, social ads, brand videos. Use for: Facebook ads, YouTube ads, product launches, brand awareness. Triggers: marketing video, ad video, promo video, commercial, brand video, product video, explainer video, ad creative, video ad, facebook ad video, youtube ad, instagram ad, tiktok ad, promotional video, launch video
- ai-music-generation101-skills
Generate AI music and songs with ElevenLabs, Diffrythm, Tencent Song Generation via inference.sh CLI. Models: ElevenLabs Music (up to 10 min, commercial license), Diffrythm (fast song generation), Tencent Song Generation (full songs with vocals). Capabilities: text-to-music, song generation, instrumental, lyrics to song, soundtrack creation. Use for: background music, social media content, game soundtracks, podcasts, royalty-free music. Triggers: music generation, ai music, generate song, ai composer, text to music, song generator, create music with ai, suno alternative, udio alternative, ai song, ai soundtrack, generate soundtrack, ai jingle, music ai, beat generator, elevenlabs music, eleven labs music
- ai-podcast101-skills
Generate multi-person talking head podcast videos from scratch using AI — character creation, TTS, avatar animation, and video stitching. Use when the user wants to create a podcast, talking head video, or multi-speaker conversation video.
- ai-podcast-creation101-skills
Create AI-powered podcasts with text-to-speech, music, and audio editing. Tools: Kokoro TTS, DIA TTS, Chatterbox, AI music generation, ffmpeg for audio assembly. Capabilities: multi-voice conversations, background music, intro/outro, full episodes. Use for: podcast production, audiobooks, voice content, audio newsletters. Triggers: podcast, ai podcast, text to speech podcast, audio content, voice over, ai audiobook, multi voice, conversation ai, notebooklm alternative, audio generation, podcast automation, ai narrator, voice content, audio newsletter, podcast maker
- ai-product-photography101-skills
Generate professional AI product photography and commercial images. Models: FLUX, Imagen 3, Grok, Seedream for product shots, lifestyle images, mockups. Capabilities: studio lighting, lifestyle scenes, packaging, e-commerce photos. Use for: e-commerce, Amazon listings, Shopify, marketing, advertising, mockups. Triggers: product photography, product shot, commercial photography, e-commerce images, amazon product photo, shopify images, product mockup, studio product shot, lifestyle product image, advertising photo, packshot, product render, product image ai
- ai-rag-pipeline101-skills
Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs. Tools: Tavily Search, Exa Search, Exa Answer, Claude, GPT-4, Gemini via OpenRouter. Capabilities: research, fact-checking, grounded responses, knowledge retrieval. Use for: AI agents, research assistants, fact-checkers, knowledge bases. Triggers: rag, retrieval augmented generation, grounded ai, search and answer, research agent, fact checking, knowledge retrieval, ai research, search + llm, web grounded, perplexity alternative, ai with sources, citation, research pipeline
- ai-social-media-content101-skills
Create AI-powered social media content for TikTok, Instagram, YouTube, Twitter/X. Generate: images, videos, reels, shorts, thumbnails, captions, hashtags. Tools: FLUX, Veo, Seedance, Wan, Kokoro TTS, Claude for copywriting. Use for: content creators, social media managers, influencers, brands. Triggers: social media content, tiktok, instagram reels, youtube shorts, twitter post, content creator, ai influencer, social content, reels, shorts, viral content, thumbnail generator, caption generator, hashtag generator, ugc content
- ai-video-generation101-skills
Generate AI videos with Google Veo, Seedance 2.0, HappyHorse, Wan, Grok and 40+ models via inference.sh CLI. Models: Veo 3.1, Seedance 2.0, HappyHorse 1.0, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Capabilities: text-to-video, image-to-video, reference-to-video, video editing, lipsync, avatar animation, video upscaling, foley sound. Use for: social media videos, marketing content, explainer videos, product demos, AI avatars. Triggers: video generation, ai video, text to video, image to video, veo, animate image, video from image, ai animation, video generator, generate video, t2v, i2v, ai video maker, create video with ai, runway alternative, pika alternative, sora alternative, kling alternative, seedance, happyhorse
- ai-voice-cloning101-skills
AI voice generation, text-to-speech, and voice synthesis via inference.sh CLI. Models: Inworld TTS-2 (100+ languages, emotion/non-verbal steering), Inworld TTS 1.5 (ultra-low latency), ElevenLabs (22+ premium voices, 32 languages), Kokoro TTS, DIA, Chatterbox, Higgs, VibeVoice for natural speech. Capabilities: multiple voices, emotions, accents, long-form narration, conversation, voice transformation, delivery mode control, character voices. Use for: voiceovers, audiobooks, podcasts, video narration, accessibility, gaming NPCs, avatar audio, UGC. Triggers: voice cloning, tts, text to speech, ai voice, voice generation, voice synthesis, voice over, narration, speech synthesis, ai narrator, elevenlabs, eleven labs, natural voice, realistic speech, voice ai, voice changer, inworld, inworld tts, character voice, npc voice
- app-store-screenshots101-skills
App Store and Google Play screenshot creation with exact platform specs. Covers iOS/Android dimensions, gallery ordering, device mockups, and preview videos. Use for: app store optimization, ASO, app screenshots, app preview, play store listing. Triggers: app store screenshots, aso, app store optimization, play store screenshots, app preview, app listing, ios screenshots, android screenshots, app store images, app mockup, device mockup, app gallery, store listing
- background-removal101-skills
Remove backgrounds from images with BiRefNet via inference.sh CLI. Model: BiRefNet (high accuracy background removal). Use for: product photos, portraits, e-commerce, transparent PNGs, photo editing. Triggers: remove background, background removal, remove bg, transparent background, cut out image, background remover, rembg, product photo editing, cutout, transparent png, bg removal, photo cutout
- book-cover-design101-skills
Book cover design with genre-specific conventions, typography rules, and AI image generation. Covers fiction and non-fiction genres, sizing, thumbnail testing, and iteration workflows. Use for: self-publishing, ebook covers, print covers, audiobook covers, cover mockups. Triggers: book cover, cover design, ebook cover, book art, novel cover, self publishing cover, kindle cover, audiobook cover, book jacket, cover illustration, fiction cover, nonfiction cover
- building-inferencesh-apps101-skills
Build and deploy applications on inference.sh. Use when getting started, understanding the platform, creating apps, configuring resources, or needing an overview of inference.sh app development. Supports both Python and Node.js. Triggers: inference.sh app, belt app, inf.yml, inference.py, inference.js, deploy app, app development, build app, create app, GPU app, VRAM, app resources, app secrets, app credentials, multi-function app
- case-study-writing101-skills
B2B case study writing with STAR framework, data visualization, and research. Covers structure, customer quotes, metrics presentation, and distribution formats. Use for: customer success stories, portfolio pieces, sales enablement, marketing content. Triggers: case study, customer story, success story, b2b case study, client testimonial, customer case study, portfolio case study, use case, customer win, results story
- character-design-sheet101-skills
Character consistency across AI-generated images with reference sheets and LoRA techniques. Covers turnaround views, expression sheets, color palettes, and style consistency tricks. Use for: character design, game art, illustration, animation, comics, visual novels. Triggers: character design, character sheet, character consistency, character reference, turnaround sheet, expression sheet, character art, consistent character, character concept, reference sheet, character creation, oc design, character bible
- chat-ui101-skills
Chat UI building blocks for React/Next.js from ui.inference.sh. Components: container, messages, input, typing indicators, avatars. Capabilities: chat interfaces, message lists, input handling, streaming. Use for: building custom chat UIs, messaging interfaces, AI assistants. Triggers: chat ui, chat component, message list, chat input, shadcn chat, react chat, chat interface, messaging ui, conversation ui, chat building blocks
- competitor-teardown101-skills
Structured competitive analysis with feature matrices, SWOT, positioning maps, and UX review. Covers research frameworks, pricing comparison, review mining, and visual deliverables. Use for: market research, competitive intelligence, investor decks, product strategy, sales enablement. Triggers: competitor analysis, competitive analysis, competitor teardown, market research, competitive intelligence, swot analysis, competitor comparison, market landscape, competitor review, competitive landscape, feature comparison, market positioning
- content-repurposing101-skills
Content atomization — turn one piece of content into many formats. Covers blog-to-thread, blog-to-carousel, podcast-to-blog, video-to-quotes, and more. Use for: content marketing, social media, multi-platform distribution, content strategy. Triggers: content repurposing, repurpose content, content atomization, content recycling, one to many content, multi platform content, cross post, adapt content, reformat content, blog to thread, blog to video, podcast to blog, content multiplication
- customer-persona101-skills
Research-backed customer persona creation with market data and avatar generation. Covers demographics, psychographics, jobs-to-be-done, journey mapping, and anti-personas. Use for: marketing strategy, product development, UX research, sales enablement, content strategy. Triggers: customer persona, buyer persona, user persona, target audience, ideal customer, customer profile, audience research, user research, icp, ideal customer profile, target market, customer avatar, audience persona
- data-visualization101-skills
Data visualization with chart selection, color theory, and annotation best practices. Covers chart types (bar, line, scatter, heatmap), axes rules, and storytelling with data. Use for: charts, graphs, dashboards, reports, presentations, infographics, data stories. Triggers: data visualization, chart, graph, data chart, bar chart, line chart, scatter plot, data viz, visualization, dashboard chart, infographic data, data presentation, chart design, plot, heatmap, pie chart alternative
- dialogue-audio101-skills
Multi-speaker dialogue audio creation with ElevenLabs and Dia TTS. Covers speaker tags, emotion control, pacing, conversation flow, and post-production. Use for: podcasts, audiobooks, explainers, character dialogue, conversational content. Triggers: dialogue audio, multi speaker, conversation audio, dia tts, two speakers, podcast audio, character voices, voice acting, dialogue generation, conversation tts, multi voice, speaker tags, dialogue recording, elevenlabs dialogue, eleven labs conversation
- elevenlabs-dialogue101-skills
ElevenLabs multi-speaker dialogue generation - create conversations with different voices in a single audio file via inference.sh CLI. Capabilities: multi-voice dialogue, script-based generation, voice direction, conversation audio. Use for: podcasts, audiobooks, explainers, tutorials, character dialogue, video scripts. Triggers: elevenlabs dialogue, eleven labs dialogue, multi speaker, conversation audio, dialogue generation, text to dialogue, multi voice, voice acting, podcast dialogue, character voices, script to audio, elevenlabs conversation, two speakers
- elevenlabs-dubbing101-skills
ElevenLabs automatic dubbing - translate and dub audio/video into 29 languages while preserving speaker voice via inference.sh CLI. Capabilities: auto speaker detection, voice-preserving translation, video dubbing, audio localization. Use for: content localization, video translation, multilingual content, international distribution. Triggers: dubbing, dub video, translate audio, video translation, audio translation, localize content, elevenlabs dubbing, eleven labs dub, multilingual dub, voice translation, auto dub, language dub, content localization
- elevenlabs-music101-skills
ElevenLabs AI music generation - create original music from text prompts via inference.sh CLI. Capabilities: text-to-music, custom duration up to 10 minutes, genre/mood/instrument control, royalty-free commercial use. Use for: background music, soundtracks, jingles, podcasts, video scores, game audio. Triggers: elevenlabs music, eleven labs music, ai music, generate music, music generation, compose music, ai composer, create song, soundtrack, background music, jingle, elevenlabs compose, music ai
- elevenlabs-sound-effects101-skills
Generate AI sound effects from text descriptions with ElevenLabs via inference.sh CLI. Capabilities: text-to-sound-effect, custom duration, royalty-free audio. Use for: video production, game audio, podcasts, films, presentations, social media. Triggers: sound effects, sfx, sound generation, ai sound effects, generate sound, foley, audio effects, sound design, text to sound, elevenlabs sound, eleven labs sfx, ambient sound, cinematic sound, game sound effects
- elevenlabs-stt101-skills
ElevenLabs speech-to-text with Scribe models and forced alignment via inference.sh CLI. Models: Scribe v1/v2 (98%+ accuracy, 90+ languages). Capabilities: transcription, speaker diarization, audio event tagging, word-level timestamps, forced alignment, subtitle generation. Use for: meeting transcription, subtitles, podcast transcripts, lip-sync timing, karaoke. Triggers: elevenlabs stt, elevenlabs transcription, scribe, elevenlabs speech to text, forced alignment, word alignment, subtitle timing, diarization, speaker identification, audio event detection, eleven labs transcribe
- elevenlabs-tts101-skills
ElevenLabs text-to-speech via inference.sh: Eleven v4 and v4 Turbo (newest, most expressive, audio tags, realtime streaming), Eleven v3, Multilingual v2 and Flash v2.5, each as its own app with 22+ premium voices. Capabilities: text-to-speech, realtime text-to-speech streaming, audio tags for emotion and delivery, voice selection, stability control, custom and cloned voices. Use for: voiceovers, audiobooks, video narration, podcasts, voice agents, accessibility, IVR. Triggers: elevenlabs, eleven labs, eleven v4, eleven v4 turbo, eleven v3, elevenlabs tts, premium tts, realtime tts, streaming tts, professional voice, ai voice, high quality tts, multilingual tts, voice generation, natural speech, realistic voice, voice over, speech synthesis
- elevenlabs-voice-changer101-skills
ElevenLabs voice changer - transform any voice to a different voice while preserving speech content and emotion via inference.sh CLI. Models: eleven_multilingual_sts_v2 (70+ languages), eleven_english_sts_v2. Capabilities: speech-to-speech, voice transformation, accent change, voice disguise. Use for: content creation, voice acting, privacy, dubbing, character voices. Triggers: voice changer, speech to speech, voice transformation, change voice, voice swap, voice conversion, voice disguise, eleven labs voice changer, elevenlabs sts, transform voice, ai voice changer, voice modifier
- elevenlabs-voice-isolator101-skills
ElevenLabs voice isolator - remove background noise and isolate vocals from audio via inference.sh CLI. Capabilities: noise removal, voice extraction, audio cleanup, background removal. Use for: podcast cleanup, interview audio, music vocals, noisy recordings, audio restoration. Triggers: voice isolator, noise removal, background removal, isolate voice, clean audio, remove background noise, audio cleanup, voice extraction, elevenlabs isolator, eleven labs noise, vocal isolation, denoise, audio restoration, voice separation
- email-design101-skills
Email marketing design with layout patterns, subject line formulas, and deliverability rules. Covers welcome sequences, promotional emails, transactional templates, and mobile optimization. Use for: email marketing, newsletter design, drip campaigns, email templates, transactional emails. Triggers: email design, email template, email marketing, newsletter design, email layout, email campaign, drip campaign, welcome email, promotional email, transactional email, email subject line, email header image, email banner
- explainer-video-guide101-skills
Explainer video production guide: scripting, voiceover, visuals, and assembly. Covers script formulas, pacing rules, scene planning, and multi-tool pipelines. Use for: product demos, how-it-works videos, onboarding videos, social explainers. Triggers: explainer video, how to make explainer, product video, demo video, video production, video script, animated explainer, product demo video, tutorial video, onboarding video, walkthrough video, video pipeline
- flux-image101-skills
Generate images with FLUX models (Black Forest Labs) via inference.sh CLI. Models: FLUX Dev LoRA, FLUX.2 Klein LoRA with custom style adaptation. Capabilities: text-to-image, image-to-image, LoRA fine-tuning, custom styles. Triggers: flux, flux.2, flux dev, flux schnell, flux pro, black forest labs, flux image, flux ai, flux model, flux lora
- google-veo101-skills
Generate videos with Google Veo models via inference.sh CLI. Models: Veo 3.1, Veo 3.1 Fast. Capabilities: text-to-video, cinematic output, high quality video generation. Triggers: veo, google veo, veo 3, veo 2, veo 3.1, vertex ai video, google video generation, google video ai, veo model, veo video
- gpt-image101-skills
Generate and edit images with OpenAI GPT-Image-2.5 and GPT-Image-2 via inference.sh CLI. Models: GPT-Image-2.5 Flare, GPT-Image-2.5 Sunburst, GPT-Image-2. Capabilities: text-to-image, image editing, inpainting, mask-based editing, multi-image reference, batch generation, transparent backgrounds. Use for: product mockups, marketing visuals, image editing, concept art, inpainting, photo manipulation. Triggers: gpt image, gpt-image-2.5, gpt image 2.5, flare, sunburst, gpt-image-2, openai image, chatgpt image, dall-e, dalle, openai image generation, gpt image edit, gpt inpainting, openai dall-e, gpt 4o image, transparent background, transparent png, remove background
- happyhorse101-skills
Generate and edit videos with Alibaba HappyHorse 1.0 models via inference.sh CLI. Models: HappyHorse T2V, I2V, R2V, Video Edit. Capabilities: text-to-video, image-to-video, reference-to-video, video editing with natural language, character preservation, 720P/1080P, up to 15 seconds. Use for: physically realistic video, video editing, character-consistent content, product demos, social media. Triggers: happyhorse, happy horse, alibaba video, happyhorse 1.0, dashscope video, alibaba happyhorse, video editing ai, ai video editor
- image-to-video101-skills
Still-to-video conversion guide: model selection, motion prompting, and camera movement. Covers Wan 2.5 i2v, Seedance, Fabric, Grok Video with when to use each. Use for: animating images, creating video from stills, adding motion, product animations. Triggers: image to video, i2v, animate image, still to video, add motion to image, image animation, photo to video, animate still, wan i2v, image2video, bring image to life, animate photo, motion from image
- image-upscaling101-skills
Upscale and enhance images with Real-ESRGAN, Thera, Topaz, FLUX Upscaler via inference.sh CLI. Models: Real-ESRGAN, Thera (any size), FLUX Dev Upscaler, Topaz Image Upscaler. Use for: enhance low-res images, upscale AI art, restore old photos, increase resolution. Triggers: upscale image, image upscaler, enhance image, increase resolution, real esrgan, ai upscale, super resolution, image enhancement, upscaling, enlarge image, higher resolution, 4k upscale, hd upscale
- infsh-cli101-skills
Run AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok
- javascript-sdk101-skills
JavaScript/TypeScript SDK for inference.sh - run AI apps, build agents, integrate with all models. Package: @inferencesh/sdk (npm install). Full TypeScript support, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, human approval. Use for: JavaScript integration, TypeScript, Node.js, React, Next.js, frontend apps. Triggers: javascript sdk, typescript sdk, npm install, node.js api, js client, react ai, next.js ai, frontend sdk, @inferencesh/sdk, typescript agent, browser sdk, js integration
- landing-page-design101-skills
Landing page conversion optimization with layout rules, hero section design, and CTA psychology. Covers above-the-fold formula, social proof placement, mobile design, and F-pattern reading. Use for: startup landing pages, product pages, SaaS marketing, conversion optimization. Triggers: landing page, hero section, above the fold, conversion optimization, landing page design, cta button, hero image, landing page layout, saas landing page, product page design, conversion rate, landing page best practices
- linkedin-content101-skills
LinkedIn post writing with hook formulas, formatting rules, and engagement patterns. Covers post types, algorithm signals, character limits, and content pillars. Use for: LinkedIn posts, professional content, thought leadership, B2B content, personal branding. Triggers: linkedin post, linkedin content, linkedin writing, linkedin strategy, linkedin engagement, linkedin algorithm, linkedin hook, linkedin formatting, thought leadership, professional content, b2b content, linkedin growth
- llm-models101-skills
Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5, Gemini 3 Pro, Kimi K2, GLM-4.6, Intellect 3. One API for all models with automatic fallback and cost optimization. Use for: AI assistants, code generation, reasoning, agents, chat, content generation. Triggers: claude api, openrouter, llm api, claude sonnet, claude opus, gemini api, kimi, language model, gpt alternative, anthropic api, ai model api, llm access, chat api, claude alternative, openai alternative
- logo-design-guide101-skills
Logo design principles and AI image generation best practices for creating logos. Covers logo types, prompting techniques, scalability rules, and iteration workflows. Use for: brand identity, startup logos, app icons, favicons, logo concepts. Triggers: logo design, create logo, brand logo, logo generation, ai logo, logo maker, icon design, brand mark, logo concept, startup logo, app icon logo
- nano-banana101-skills
Generate images with Google Gemini native image models via inference.sh CLI. Models: Gemini 3 Pro Image, Gemini 2.5 Flash Image. Capabilities: text-to-image, image editing, multi-image input. Triggers: nano banana, gemini image, gemini 3 pro image, gemini 2.5 flash image, google image generation, native image generation, gemini native image
- nano-banana-2101-skills
Generate images with Google Gemini 3.1 Flash Image Preview (Nano Banana 2) via inference.sh CLI. Capabilities: text-to-image, image editing, multi-image input (up to 14 images), Google Search grounding. Triggers: nano banana 2, nanobanana 2, gemini 3.1 flash image, gemini 3 1 flash image preview, google image generation
- newsletter-curation101-skills
Newsletter curation with content sourcing, editorial structure, and subscriber growth strategies. Covers issue formatting, link roundups, commentary style, and sending cadence. Use for: email newsletters, link roundups, weekly digests, curated content, creator newsletters. Triggers: newsletter, email newsletter, newsletter curation, weekly digest, link roundup, curated newsletter, newsletter writing, newsletter format, subscriber growth, newsletter strategy, content curation, newsletter template
- og-image-design101-skills
Open Graph and social sharing image design with platform specs, text placement, and branding. Covers OG meta tags, Twitter cards, LinkedIn previews, and dynamic generation. Use for: social sharing images, blog thumbnails, link previews, social cards. Triggers: og image, open graph, social sharing image, twitter card, social card, link preview image, og meta, sharing preview, social thumbnail, meta image, og:image, twitter:image, linkedin preview
- p-image101-skills
Generate images with Pruna P-Image models via inference.sh CLI. Models: P-Image, P-Image-LoRA, P-Image-Edit, P-Image-Edit-LoRA. Capabilities: text-to-image, image editing, LoRA styles, multi-image compositing, fast inference. Pruna optimizes models for speed without quality loss. Triggers: pruna, p-image, pruna image, fast image generation, optimized flux, pruna ai, p image, fast ai image, economic image generation, cheap image generation
- p-video101-skills
Generate videos with Pruna P-Video and WAN models via inference.sh CLI. Models: P-Video, WAN-T2V, WAN-I2V. Capabilities: text-to-video, image-to-video, audio support, 720p/1080p, fast inference. Pruna optimizes models for speed without quality loss. Triggers: pruna video, p-video, pruna ai video, fast video generation, optimized video, wan t2v, wan i2v, economic video generation, cheap video generation, pruna text to video, pruna image to video
- p-video-avatar101-skills
Generate talking head avatar videos with Pruna P-Video-Avatar via inference.sh CLI. Turn a portrait image into a realistic speaking video with built-in TTS. 18x faster and 6x cheaper than competitors. Models: P-Video-Avatar, P-Image (for portrait generation). Capabilities: text-to-avatar, audio-driven avatars, 30 voices, 10 languages, 720p/1080p, built-in TTS, dynamic backgrounds, full-body control. Use for: AI presenters, product demos, explainer videos, virtual influencers, marketing, education, multilingual content, UGC, gaming avatars. Triggers: avatar video, talking head, ai avatar, p-video-avatar, pruna avatar, video avatar, ai presenter, digital human, virtual presenter, lipsync, talking avatar, ai spokesperson, heygen alternative, synthesia alternative, veed alternative, fabric alternative, omnihuman alternative
- pitch-deck-visuals101-skills
Investor pitch deck structure with slide-by-slide framework, visual design rules, and data presentation. Covers the 12-slide framework, chart types, team slides, and common investor turn-offs. Use for: fundraising decks, investor presentations, startup pitch, demo day, grant proposals. Triggers: pitch deck, investor deck, startup pitch, fundraising deck, demo day, pitch presentation, investor presentation, seed deck, series a deck, pitch slides, startup presentation, vc pitch, investor meeting
- press-release-writing101-skills
Press release writing in AP style with inverted pyramid structure. Covers formatting, datelines, quotes, boilerplates, and fact-checking. Use for: product launches, funding announcements, partnerships, company news, events. Triggers: press release, pr writing, media release, news release, announcement, product launch announcement, funding announcement, company news, media advisory, ap style, press statement, news wire
- product-changelog101-skills
Product changelog and release notes that users actually read. Covers categorization, user-facing language, visuals, and distribution. Use for: release notes, changelogs, product updates, feature announcements, versioning. Triggers: changelog, release notes, product update, version notes, what's new, feature announcement, product changelog, update log, release announcement, version release, product release, ship notes
- product-hunt-launch101-skills
Product Hunt launch optimization with specific specs, timing, and gallery strategy. Covers taglines, gallery images, maker comments, and launch day tactics. Use for: product launches, startup launches, side project launches, Product Hunt optimization. Triggers: product hunt, ph launch, product hunt launch, launch strategy, product launch, startup launch, product hunt tips, product hunt gallery, ph optimization, launch day, product hunt maker
- product-photography101-skills
AI product photography with studio lighting, lifestyle shots, and packshot conventions. Covers angles, backgrounds, shadow types, hero shots, and e-commerce image requirements. Use for: product photos, e-commerce images, Amazon listings, packshots, lifestyle photography. Triggers: product photography, product photo, packshot, e-commerce photography, product shot, product image, studio photography, lifestyle product, amazon product photo, product listing image, hero shot, product mockup, commercial photography
- prompt-engineering101-skills
Master prompt engineering for AI models: LLMs, image generators, video models. Techniques: chain-of-thought, few-shot, system prompts, negative prompts. Models: Claude, GPT-4, Gemini, FLUX, Veo, Stable Diffusion prompting. Use for: better AI outputs, consistent results, complex tasks, optimization. Triggers: prompt engineering, how to prompt, better prompts, prompt tips, prompting guide, llm prompting, image prompt, ai prompting, prompt optimization, prompt template, prompt structure, effective prompts, prompt techniques
- python-executor101-skills
Execute Python code in a safe sandboxed environment via [inference.sh](https://inference.sh). Pre-installed: NumPy, Pandas, Matplotlib, requests, BeautifulSoup, Selenium, Playwright, MoviePy, Pillow, OpenCV, trimesh, and 100+ more libraries. Use for: data processing, web scraping, image manipulation, video creation, 3D model processing, PDF generation, API calls, automation scripts. Triggers: python, execute code, run script, web scraping, data analysis, image processing, video editing, 3D models, automation, pandas, matplotlib
- python-sdk101-skills
Python SDK for inference.sh - run AI apps, build agents, and integrate with all models. Package: inferencesh (pip install inferencesh). Supports sync/async, streaming, file uploads. Build agents with template or ad-hoc patterns, tool builder API, skills, and human approval. Use for: Python integration, AI apps, agent development, RAG pipelines, automation. Triggers: python sdk, inferencesh, pip install, python api, python client, async inference, python agent, tool builder python, programmatic ai, python integration, sdk python
- qwen-image-2101-skills
Generate and edit images with Alibaba Qwen-Image-2.0 models via inference.sh CLI. Models: Qwen-Image-2.0 (fast), Qwen-Image-2.0-Pro (professional text rendering). Capabilities: text-to-image, multi-image editing, complex text rendering. Triggers: qwen image, qwen-image, alibaba image, dashscope image, qwen image 2, qwen image pro
- qwen-image-2-pro101-skills
Generate images with Alibaba Qwen-Image-2.0-Pro via inference.sh CLI. Professional text rendering, fine-grained realism, enhanced semantic adherence. Ideal for posters, banners, and text-heavy designs. Triggers: qwen image pro, qwen-image-pro, qwen 2 pro, alibaba image pro, dashscope pro, professional text rendering
- related-skill101-skills
Discover and install related skills from inference.sh skill registry. Helps find complementary skills for your AI workflow. Use for: skill discovery, workflow expansion, capability exploration. Triggers: related skills, find skills, skill discovery, complementary skills, expand workflow, more capabilities, similar skills, skill suggestions
- remotion-render101-skills
Render videos from React/Remotion component code via inference.sh. Pass TSX code, get MP4. Supports all Remotion APIs: useCurrentFrame, useVideoConfig, spring, interpolate, AbsoluteFill, Sequence. Configurable resolution, FPS, duration, codec. Use for: programmatic video generation, animated graphics, motion design, data-driven videos, React animations to video. Triggers: remotion, render video from code, tsx to video, react video, programmatic video, remotion render, code to video, animated video, motion graphics code, react animation video
- seedance101-skills
Generate videos with ByteDance Seedance 2.0 via inference.sh CLI. Unified model for text-to-video, image-to-video, and reference-to-video with synchronized audio, up to 1080p, 4-15s duration. Pro and Fast variants. Studio variants with private asset library for portrait consistency. Use for: social media videos, music videos, product demos, animated content, AI video with sound. Triggers: seedance, seedance 2, bytedance video, seedance t2v, seedance i2v, seedance r2v, video with audio, seedance 2.0, bytedance seedance, seedance studio
- seo-content-brief101-skills
SEO content brief creation with keyword research, search intent analysis, and content structure. Covers SERP analysis, heading hierarchy, word count targets, and internal linking strategy. Use for: content briefs, SEO writing, blog strategy, content planning, keyword targeting. Triggers: seo content brief, content brief, seo brief, keyword research, search intent, content strategy, blog brief, seo writing, content planning, keyword targeting, serp analysis, content outline, seo article, blog seo
- social-media-carousel101-skills
Multi-slide carousel design for Instagram, LinkedIn, and Twitter/X with layout rules and hooks. Covers slide structure, text hierarchy, swipe psychology, and platform-specific specs. Use for: carousel posts, Instagram carousels, LinkedIn carousels, slide posts, educational content. Triggers: carousel, instagram carousel, linkedin carousel, slide post, carousel design, swipe post, multi-image post, carousel template, educational carousel, carousel content, instagram slides, linkedin slides
- speech-to-text101-skills
Transcribe audio to text with ElevenLabs Scribe and Whisper models via inference.sh CLI. Models: ElevenLabs Scribe v2 (98%+ accuracy, diarization), Fast Whisper Large V3, Whisper V3 Large. Capabilities: transcription, translation, multi-language, timestamps, speaker diarization, audio event tagging. Use for: meeting transcription, subtitles, podcast transcripts, voice notes. Triggers: speech to text, transcription, whisper, audio to text, transcribe audio, voice to text, stt, automatic transcription, subtitles generation, transcribe meeting, audio transcription, whisper ai, elevenlabs stt, scribe, eleven labs transcribe
- storyboard-creation101-skills
Film and video storyboarding with shot vocabulary, continuity rules, and panel layout. Covers shot types, camera angles, movement, 180-degree rule, and annotation format. Use for: video planning, film pre-production, ad storyboards, music video planning, animation. Triggers: storyboard, storyboarding, shot list, film planning, video planning, pre production, shot composition, camera angles, scene planning, visual script, animatic, storyboard panels, video storyboard
- talking-head-production101-skills
Talking head video production with AI avatars, lipsync, and voiceover. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also covers OmniHuman, PixVerse, Fabric. Portrait requirements, audio quality, production workflows. Use for: spokesperson videos, course content, social media, presentations, demos. Triggers: talking head, avatar video, lipsync, lip sync, ai spokesperson, virtual presenter, ai presenter, omnihuman, talking avatar, video presenter, ai talking head, presenter video, ai face video, p-video-avatar
- technical-blog-writing101-skills
Technical blog post writing with structure, code examples, and developer audience conventions. Covers post types, code formatting, explanation depth, and developer-specific engagement patterns. Use for: engineering blogs, dev tutorials, technical writing, developer content, documentation posts. Triggers: technical blog, dev blog, engineering blog, technical writing, developer tutorial, tech post, code tutorial, programming blog, developer content, technical article, engineering post, coding tutorial, technical content
- text-to-speech101-skills
Convert text to natural speech with Inworld TTS, ElevenLabs, DIA TTS, Kokoro, Chatterbox, and more via inference.sh CLI. Models: Inworld TTS-2 (100+ languages, emotion steering), Inworld TTS 1.5 (ultra-low latency), ElevenLabs (premium, 22+ voices, 32 languages), DIA TTS (conversational), Kokoro TTS, Chatterbox, Higgs Audio, VibeVoice (podcasts). Capabilities: text-to-speech, voice cloning, multi-speaker dialogue, podcast generation, expressive speech, emotion/delivery steering, character voices. Use for: voiceovers, audiobooks, podcasts, accessibility, video narration, IVR, voice assistants, gaming characters, avatar audio. Triggers: text to speech, tts, voice generation, ai voice, speech synthesis, voice over, generate speech, ai narrator, voice cloning, text to audio, elevenlabs, eleven labs, voice ai, ai voiceover, speech generator, natural voice, inworld, inworld tts, character voice, game voice, npc voice
- tools-ui101-skills
Tool lifecycle UI components for React/Next.js from ui.inference.sh. Display tool calls: pending, progress, approval required, results. Capabilities: tool status, progress indicators, approval flows, results display. Use for: showing agent tool calls, human-in-the-loop approvals, tool output. Triggers: tool ui, tool calls, tool status, tool approval, tool results, agent tools, mcp tools ui, function calling ui, tool lifecycle, tool pending
- twitter-automation101-skills
Automate Twitter/X with posting, engagement, and user management via inference.sh CLI. Apps: x/post-create (text and media), x/post-like, x/post-retweet, x/dm-send, x/user-follow. Capabilities: post tweets, schedule content, like posts, retweet, send DMs, follow users, get profiles. Use for: social media automation, content scheduling, engagement bots, audience growth, X API. Triggers: twitter api, x api, tweet automation, post to twitter, twitter bot, social media automation, x automation, tweet scheduler, twitter integration, post tweet, twitter post, x post, send tweet
- twitter-thread-creation101-skills
Twitter/X thread writing with hook tweets, thread structure, and engagement optimization. Covers tweet formatting, character limits, media attachments, and posting strategies. Use for: Twitter threads, X posts, tweet storms, Twitter content, social media writing. Triggers: twitter thread, tweet thread, x thread, twitter post, tweet writing, thread creation, tweet storm, twitter content, x post, twitter writing, twitter hook, tweet formatting, thread structure
- video-ad-specs101-skills
Video ad creation with exact platform-specific specs for TikTok, Instagram, YouTube, Facebook, LinkedIn. Covers dimensions, duration limits, AIDA framework, and caption requirements. Use for: video ads, social media ads, paid media creative, video marketing, ad production. Triggers: video ad, social media ad, tiktok ad, instagram ad, youtube ad, facebook ad, linkedin ad, video creative, ad specs, paid media, video marketing, ad production, reels ad, stories ad, pre roll, bumper ad
- video-prompting-guide101-skills
Best practices and techniques for writing effective AI video generation prompts. Covers: Veo, Seedance, Wan, Grok, Kling, Runway, Pika, Sora prompting strategies. Learn: shot types, camera movements, lighting, pacing, style keywords, negative prompts. Use for: improving video quality, getting consistent results, professional video prompts. Triggers: video prompt, how to prompt video, veo prompts, video generation tips, better ai video, video prompt engineering, video prompt guide, video prompt template, ai video tips, video prompt best practices, video prompt examples, cinematography prompts
- web-search101-skills
Web search and content extraction with Tavily and Exa via inference.sh CLI. Apps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract. Capabilities: AI-powered search, content extraction, direct answers, research. Use for: research, RAG pipelines, fact-checking, content aggregation, agents. Triggers: web search, tavily, exa, search api, content extraction, research, internet search, ai search, search assistant, web scraping, rag, perplexity alternative
- widgets-ui101-skills
Declarative UI widgets from JSON for React/Next.js from ui.inference.sh. Render rich interactive UIs from structured agent responses. Capabilities: forms, buttons, cards, layouts, inputs, selects, checkboxes. Use for: agent-generated UIs, dynamic forms, data display, interactive cards. Triggers: widgets, declarative ui, json ui, widget renderer, agent widgets, dynamic ui, form widgets, card widgets, shadcn widgets, structured output ui
- youtube-thumbnail-design101-skills
YouTube thumbnail design with specific dimensions, contrast rules, and mobile preview optimization. Covers safe zones, text placement, face expression psychology, and A/B testing. Use for: YouTube thumbnails, video cover images, click-through optimization. Triggers: youtube thumbnail, thumbnail design, video thumbnail, click through rate, ctr optimization, youtube cover, video cover image, thumbnail maker, thumbnail tips, youtube design, video preview image
api-and-interface-designaddyosmaniGuides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend.
- browser-testing-with-devtoolsaddyosmani
Tests in real browsers via Chrome DevTools MCP. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data. Requires the chrome-devtools MCP server to be configured.
- ci-cd-and-automationaddyosmani
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.
- code-review-and-qualityaddyosmani
Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch. Use when asked to review a diff or a pull request, even when the diff is pasted inline.
- code-simplificationaddyosmani
Simplifies code for clarity. Use when refactoring code for clarity without changing behavior. Use when code works but is harder to read, maintain, or extend than it should be. Use when reviewing code that has accumulated unnecessary complexity.
- constraint-driven-developmentaddyosmani
Establishes a project's quality bar as a written contract and stops agents quietly lowering it. Interviews the user on which dimensions matter, supplies sane default thresholds when they have no number in mind, records everything in CONSTRAINTS.md, and watches the diff for a weakened bar — new @ts-ignore or eslint-disable suppressions, skipped or deleted tests, assertions stripped out, unimplemented stubs, thresholds edited down. Use when no quality bar is written down, when the user says "set up constraints" or "define our standards", when the user wants dimensions they care about — accessibility, web performance, coverage — set up as enforced constraints, when an agent keeps silencing checks or skipping tests to get to green, when you need a coverage or performance threshold and don't know what number to pick, or when an agent writes more code than anyone will read.
- context-engineeringaddyosmani
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
- debugging-and-error-recoveryaddyosmani
Guides systematic root-cause debugging. Use when tests fail, builds break, something that worked yesterday broke, behavior doesn't match expectations, or you encounter any unexpected error. Use when you need to figure out what broke and why — a systematic approach to finding and fixing the root cause rather than guessing.
- deprecation-and-migrationaddyosmani
Manages deprecation and migration. Use when removing old systems, APIs, or features. Use when migrating users from one implementation to another. Use when migrating a database schema in production, such as renaming or dropping a column without downtime (expand/contract). Use when deciding whether to maintain or sunset existing code.
- documentation-and-adrsaddyosmani
Records decisions and documentation. Use when you need to document an architecture decision (ADR) or the reasoning behind a design choice, when changing public APIs, shipping features, or when you need to record context that future engineers and agents will need to understand the codebase.
- doubt-driven-developmentaddyosmani
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high (production auth, security-sensitive logic, a high-stakes migration, irreversible operations), or any time a confident output would be cheaper to verify now than to debug later.
- frontend-ui-engineeringaddyosmani
Builds production-quality, accessible, responsive user-facing UIs. Use when building or modifying interfaces and pages, creating components, implementing layouts, meeting WCAG accessibility requirements, managing state, or when the output needs to look and feel production-quality rather than AI-generated.
- git-workflow-and-versioningaddyosmani
Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, splitting uncommitted work in a messy working tree into clean atomic commits, opening or reviewing a pull request (PR), pushing to a remote, or when you need to organize work across multiple parallel streams. Use when cutting a release, choosing a semantic version bump, tagging, or writing a changelog.
- idea-refineaddyosmani
Refines raw ideas into sharp, actionable concepts through structured divergent and convergent thinking. Use when an idea is still vague, when you need to stress-test assumptions before committing to a plan, or when you want to expand options before converging on one. Triggers on "ideate", "refine this idea", or "stress-test my plan".
- incremental-implementationaddyosmani
Delivers changes incrementally in thin, verifiable slices. Use when implementing any feature or change that touches more than one file, or when picking up the next task from a plan. Use when rolling a change out behind a feature flag, when you're about to write a large amount of code at once, or when a task feels too big to land in one step.
- interview-meaddyosmani
Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invokes ("interview me", "grill me", "are we sure?", "stress-test my thinking"), or when you catch yourself silently filling in ambiguous requirements before any plan, spec, or code exists.
- observability-and-instrumentationaddyosmani
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
- performance-optimizationaddyosmani
Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.
- planning-and-task-breakdownaddyosmani
Breaks work into ordered tasks. Use when you have a spec or clear requirements and need to break work into implementable tasks. Use when a task feels too large to start, when you need to estimate scope, or when parallel work is possible.
- security-and-hardeningaddyosmani
Hardens code against vulnerabilities. Use when auditing an input handler for vulnerabilities, when handling user input, authentication, data storage, or external integrations, or when checking a login flow is safe against the OWASP Top Ten. Use when building any feature that accepts untrusted data, manages user sessions, or interacts with third-party services. Use when auditing dependencies for known vulnerabilities, triaging package-manager audit findings, or assessing supply-chain risk in a new package. Use when personal data or privacy compliance (GDPR, CCPA) is involved.
- shipping-and-launchaddyosmani
Prepares production launches. Use when preparing to deploy to production, or when asking what needs to be in place before shipping. Use when you need a pre-launch checklist, when setting up monitoring, when planning a staged rollout, or when you need a rollback strategy.
- source-driven-developmentaddyosmani
Grounds every implementation decision in official documentation. Use when you want to verify an approach against the official docs before implementing it, or when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.
- spec-driven-developmentaddyosmani
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when drafting a PRD or requirements document with objectives and scope, or when requirements are unclear, ambiguous, or only exist as a vague idea. Use when a single requirement spans several independently testable capabilities and needs decomposing into a capability map of modules before specifying.
- test-driven-developmentaddyosmani
Drives development with tests using the red-green-refactor loop. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality. Use when asked to add tests to a function, fix a bug in it or change its behavior, even when the code is pasted inline and the request does not mention tests.
- using-agent-skillsaddyosmani
Discovers and invokes agent skills. Use when starting a session, or when you need to decide which skill or workflow applies to the piece of work at hand. This is the meta-skill that governs how all other skills are discovered and invoked.
agentix-ceoagentix-cloudManage your team — create roles, assign tasks, spawn workers, and monitor progress
agentspaceagentspace-soSee what your AI agent is doing, from anywhere. The agent keeps writing — logs, code, generated outputs, screenshots, artifacts. One command turns the folder into a live URL you (or a teammate) open in any browser to watch files evolve, edit in place, or comment — no sync, no zip, no account. Workspaces stay live 24 hours anonymously; one email claim keeps them permanent. Hosted on Cloudflare. Triggers on "show me what the agent is doing", "open the agent's folder", "share this folder", "give me a link", "hand off this workspace", or any ask to make an agent's local file state visible from another device or to another person.
- find-skillsagentspace-so
Discover, vet, and install agent skills by searching ACROSS every major registry at once — skills.sh, clawhub.ai, and GitHub — presenting each board on its own native metric (installs / stars) with the top entry per board, security-scanning the top candidates' real SKILL.md for risky patterns, and flagging what's already installed. Use when the user asks "how do I do X", "find a skill for X", "is there a skill that…", "what skill should I install for…", or wants to extend the agent with a capability that might already exist as a published skill. Unlike single-registry search, this surfaces the best of every platform side by side, so you recommend the genuinely relevant, popular, well-maintained, and SAFE one — not whatever ranked first on one site.
huashu-agent-swarmalchaincyf多Agent蜂群并行协作，纯git自组织，适合大型项目开发。当用户提到"蜂群模式"、"多agent"、"并行开发"、"agent swarm"时使用。
- huashu-article-editalchaincyf
标准化文章编辑流程，确保修改范围明确、进度可追踪、变更有记录。当用户说"编辑文章"、"修改文章"、"调整内容"、"改一下这篇"时使用此技能。
- huashu-article-to-xalchaincyf
长文精简为X平台内容（200-500字），保留核心观点和个人风格。当用户提到"转微博"、"发小红书"、"社交媒体"、"缩短文章"时使用。
- huashu-data-proalchaincyf
数据分析与办公提效全能助手。覆盖数据处理、分析洞察、报告撰写、PPT制作、数据可视化的端到端工作流。 始终从专家视角出发，帮用户多想一步。遇到不确定的问题主动与用户确认。 支持：Excel数据分析、投放数据复盘、ROI测算、数据可视化、报告生成、PPT制作、公式生成。 当用户提到"分析数据"、"做报告"、"做PPT"、"Excel"、"投放分析"、"ROI"、"复盘"、 "周报"、"月报"、"数据处理"、"图表"、"可视化"、"汇报"、"表格"、"公式"时使用此技能。
- huashu-designalchaincyf
设计哲学顾问，从20种风格中推荐3个方向并生成视觉Demo和AI提示词。当用户提到"设计风格"、"设计方向"、"配色方案"、"视觉风格"、"设计评审"、"推荐风格"时使用。
- huashu-douyin-scriptalchaincyf
抖音爆款脚本创作工作流。从竞品视频拆解到脚本生成的完整流程：下载抖音视频→Gemini视频分析→爆款公式提炼→脚本+分镜生成→AI味审校。 当用户提到"抖音脚本"、"爆款拆解"、"竞品分析"、"带货脚本"、"千川素材"、"种草脚本"、"视频拆解"、"抖音视频分析"时使用此技能。
- huashu-image-uploadalchaincyf
文章配图一键生成并上传图床，自动插入Markdown链接。当用户提到"配图"、"插图"、"上传图片"、"文章配图"时使用。
- huashu-info-searchalchaincyf
多渠道搜索新产品新技术，交叉验证后存入知识库。当用户提到"最新信息"、"新产品"、"搜索资料"、"查资料"、"了解XX"时使用。
- huashu-material-searchalchaincyf
搜索个人素材库1800+条真实经历和观点，为内容增加人味。当用户提到"个人经历"、"真实案例"、"素材"、"人味"时使用。
- huashu-md-to-pdfalchaincyf
将 Markdown 文档转换为专业的 PDF 白皮书，采用苹果设计风格。 支持完整的 Markdown 语法（代码块、表格、引用、列表等）。 自动生成封面、目录、页眉页脚。 使用场景：技术文档、白皮书、教程、报告等需要专业排版的 Markdown 文档。
- huashu-prompt-savealchaincyf
自动识别Prompt类型并分类保存（技术/内容/教学/产品/通用）。当用户提到"保存prompt"、"记录prompt"、"整理prompt"时使用。
- huashu-proofreadingalchaincyf
三遍审校降低AI检测率，让文章更有人味。当用户提到"AI味太重"、"像AI写的"、"降低AI检测率"、"审校"、"自然一些"时使用。
- huashu-researchalchaincyf
结构化网络调研流程，确保调研成果增量保存到文件，不因会话截断丢失。当用户说"调研"、"搜索资料"、"帮我查一下"、"了解一下"、"最新信息"时使用此技能。
- huashu-script-polishalchaincyf
视频脚本口语化审校，去书面腔让脚本适合说出来。当用户提到"口语化"、"太书面了"、"像说话一样"、"脚本审校"时使用。
- huashu-skill-updateralchaincyf
检查并更新花叔系 skills。用户说「检查skill更新」「更新花叔的skill」「skill是不是最新的」时触发。按各仓库的版本标签判断有没有新版本，只提示，是否更新由用户决定。
- huashu-slidesalchaincyf
从内容到成品PPTX的端到端演示文稿制作，含AI插画生成和18种设计风格。当用户提到"做PPT"、"做幻灯片"、"演示文稿"、"Keynote"、"slides"时使用。
- huashu-speech-coachalchaincyf
演讲与分享教练。基于Patrick Winston（MIT AI教授）的How to Speak方法论，帮助准备线下培训、技术分享、B站教程视频等演讲场景。当用户提到"演讲"、"分享"、"培训"、"讲课"、"PPT演讲"、"开场"、"结尾"、"如何讲"、"演讲结构"时使用此技能。
- huashu-topic-genalchaincyf
快速生成3-4个选题方向，含标题、大纲和优劣分析。当用户提到"选题"、"写什么"、"文章方向"、"题目建议"时使用。
- huashu-video-checkalchaincyf
基于MrBeast策略检查视频标题、封面和开头钩子。当用户提到"视频标题"、"封面图"、"点击率"、"CTR"、"观看时长"时使用。
- huashu-video-outlinealchaincyf
快速生成2-3个视频大纲方案，含标题、封面建议和结构设计。当用户提到"视频大纲"、"视频结构"、"脚本大纲"、"视频选题"时使用。
- huashu-wechat-imagealchaincyf
为微信公众号文章生成高质量配图。支持封面图（2.35:1）、正文插图（16:9/4:3）、信息图。提供两条路径：AI生成（视觉创意型）和HTML渲染（文字精确型）。当用户提到"公众号配图"、"公众号封面"、"文章配图"、"正文插图"、"公众号图片"时使用此技能。
- huashu-xhs-imagealchaincyf
为小红书笔记生成高质量配图。默认AI生成（Gemini），仅精确数据表格用HTML兜底。当用户提到"小红书配图"、"小红书封面"、"小红书图片"、"做张小红书图"、"笔记配图"时使用此技能。
angular-developerangularGenerates Angular code and provides architectural guidance. Trigger when creating projects, components, services, or HTTP communication, or for best practices on reactivity (signals, linkedSignal, resource, httpResource), queries and content projection, forms, dependency injection, routing, server and hybrid rendering (SSR, prerendering, hydration), accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, naming conventions, or CLI tooling.
- angular-new-appangular
Creates a new Angular app using the Angular CLI. This skill should be used whenever a user wants to create a new Angular application and contains important guidelines for how to effectively create a modern Angular application.
antfuantfuAnthony Fu's opinionated tooling and conventions for JavaScript/TypeScript projects. Use when setting up new projects, configuring ESLint/Prettier alternatives, monorepos, library publishing, or when the user mentions Anthony Fu's preferences.
- antfu-create-prantfu
Create a reviewable GitHub pull request from the current branch with a Conventional Commits title, a concise evidence-based body, and before/after screenshots for UI changes. Use when asked to open, create, publish, or prepare a PR.
- antfu-designantfu
antfu-style design conventions, broadened. UnoCSS-first, class-based semantic tokens with dual light/dark for tooling and devtools UIs, plus design-read, anti-slop, and micro-interaction polish for landing pages and product surfaces. Use when building or refactoring any interface with UnoCSS.
- antfu-issue-triageantfu
Triage open issues and PRs of the current GitHub repo - find already-fixed, duplicate, and spam items, suggest labels, gauge demand from reactions and comments, then present a table of proposed actions and comments for confirmation before touching anything. Use when asked to triage, organize, clean up, or groom issues and PRs.
- nitroantfu
Nitro is the framework-agnostic server toolkit (powering Nuxt) for building and deploying web servers anywhere. Use when working with nitro.config, server routes/event handlers, route rules, caching, storage, tasks, websockets, or deploying to Node/Bun/Deno/Cloudflare/Vercel.
- nuxtantfu
Nuxt full-stack Vue framework with SSR, auto-imports, and file-based routing. Use when working with Nuxt apps, server routes, useFetch, middleware, or hybrid rendering.
- piniaantfu
Pinia official Vue state management library, type-safe and extensible. Use when defining stores, working with state/getters/actions, or implementing store patterns in Vue apps.
- pnpmantfu
Node.js package manager with strict dependency resolution. Use when running pnpm specific commands, configuring workspaces via pnpm-workspace.yaml, or managing dependencies with catalogs, patches, overrides, config dependencies, or the global virtual store.
- slidevantfu
Create and present web-based slidedecks for developers using Slidev with Markdown, Vue components, code highlighting, animations, and interactive features. Use when building technical presentations, conference talks, code walkthroughs, teaching materials, or developer decks.
- tsdownantfu
Bundle TypeScript and JavaScript libraries with blazing-fast speed powered by Rolldown. Use when building libraries, generating type declarations, bundling for multiple formats, or migrating from tsup.
- turborepoantfu
Turborepo monorepo build system guidance. Triggers on: turbo.json, task pipelines, dependsOn, caching, remote cache, the "turbo" CLI, --filter, --affected, CI optimization, environment variables, internal packages, monorepo structure/best practices, and boundaries. Use when user: configures tasks/workflows/pipelines, creates packages, sets up monorepo, shares code between apps, runs changed/affected packages, debugs cache, or has apps/packages directories.
- unocssantfu
UnoCSS instant atomic CSS engine, superset of Tailwind CSS. Use when configuring UnoCSS, writing utility rules, shortcuts, or working with presets like Wind, Icons, Attributify.
- viteantfu
Vite build tool configuration, plugin API, SSR, and Vite 8 Rolldown migration. Use when working with Vite projects, vite.config.ts, Vite plugins, or building libraries/SSR apps with Vite.
- vitepressantfu
VitePress static site generator powered by Vite and Vue. Use when building documentation sites, configuring themes, or writing Markdown with Vue components.
- vitestantfu
Vitest fast unit testing framework powered by Vite with Jest-compatible API. Use when writing tests, mocking, configuring coverage, or working with test filtering and fixtures.
- vueantfu
Vue 3 Composition API, script setup macros, reactivity system, and built-in components. Use when writing Vue SFCs, defineProps/defineEmits/defineModel, watchers, or using Transition/Teleport/Suspense/KeepAlive.
- vue-best-practicesantfu
MUST be used for Vue.js tasks. Strongly recommends Composition API with `<script setup>` and TypeScript as the standard approach. Covers Vue 3, SSR, Volar, vue-tsc. Load for any Vue, .vue files, Vue Router, Pinia, or Vite with Vue work. ALWAYS use Composition API unless the project explicitly requires Options API.
Vue Router 4 patterns, navigation guards, route params, and route-component lifecycle interactions.
Use for Vue.js testing. Covers Vitest, Vue Test Utils, component testing, mocking, testing patterns, and Playwright for E2E testing.
- vueuse-functionsantfu
Apply VueUse composables where appropriate to build concise, maintainable Vue.js / Nuxt features.
Review UI code for Web Interface Guidelines compliance. Use when asked to "review my UI", "check accessibility", "audit design", "review UX", or "check my site against best practices".
academy-guideanthropicStop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.
- algorithmic-artanthropic
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
- brand-guidelinesanthropic
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
- canvas-designanthropic
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
- claude-apianthropic
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).
- discernment-nudgeanthropic
After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.
- doc-coauthoringanthropic
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
- docxanthropic
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx or .dotx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
- frontend-designanthropic
Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.
- internal-commsanthropic
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).
- mcp-builderanthropic
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
- pdfanthropic
Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
- pptxanthropic
Use this skill any time a .pptx or .potx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx or .potx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates (.potx), layouts, speaker notes, or comments. Trigger whenever the user mentions \"deck,\" \"slides,\" \"presentation,\" or references a .pptx or .potx filename, regardless of what they plan to do with the content afterward. If a .pptx or .potx file needs to be opened, created, or touched, use this skill.
- skill-creatoranthropic
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
- slack-gif-creatoranthropic
Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like "make me a GIF of X doing Y for Slack.
- template-skillanthropic
Replace with description of the skill and when Claude should use it.
- theme-factoryanthropic
Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.
- web-artifacts-builderanthropic
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, routing, or shadcn/ui components - not for simple single-file HTML/JSX artifacts.
- webapp-testinganthropic
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
- xlsxanthropic
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
anti-detect-browserantibrowDrive Chromium from standard Playwright APIs with a real-device fingerprint applied in the kernel, one persistent isolated profile per identity, and a per-profile proxy whose exit IP sets timezone and WebRTC - JavaScript (npm 'anti-detect-browser') or Python (PyPI 'antibrow'). Use when sessions must stay logged in across runs and stay separate, when a scraper or agent is blocked by an incoherent headless fingerprint, when checking ads or pricing from another region, when a page must be reached as a phone rather than a desktop, when automation mints a profile per task, when running several of your own accounts from one machine, or when testing how your own bot detection scores a real device. Also for 'antibrow', 'fingerprint browser', 'multi-account browser', '防关联', '多账号', '安卓模拟', 'Android profile', 'mobile fingerprint', 'temporary profile', 'CreepJS', 'residential proxy', 'browser-use', 'crawl4ai'. MCP control is browser-mcp-agent; isolation is multi-account-isolation.
- browser-mcp-agentantibrow
Give an AI agent its own real browser over MCP tool calls - launch, navigate, click, fill, screenshot, extract text, run JS - with a kernel-level real-device fingerprint and a persistent profile, so the session stays logged in between runs and pages see one coherent device instead of a headless build. No Playwright or SDK code to write. Use when an agent should operate a site itself, when a computer-use / browser-use setup needs a captured real fingerprint rather than a synthetic one, when agent sessions keep losing their login, or when comparing hosted agent-browser services. Also for 'MCP browser', 'browser MCP server', 'let my agent browse the web', 'agent browser control', 'browser-use MCP', 'computer use browser', 'Browserbase alternative', 'Steel browser alternative', 'headless browser detected'. Node (npx) or Python; Windows x64, macOS Intel + Apple Silicon, Linux x64 / arm64. SDK and REST reference is anti-detect-browser; account isolation is multi-account-isolation.
- multi-account-isolationantibrow
Verify that browser profiles are actually isolated from one another instead of assuming it - confirm each profile's timezone agrees with its own exit IP, that WebRTC exposes only the proxy, that canvas and WebGL hashes stay identical across relaunches of one profile, and that no two profiles share a persona, a cookie jar, or an address. Use when several of your own accounts or test identities run from one machine and the setup needs checking, when a profile tested clean but something still looks off, when choosing which detection suites to run (CreepJS, whoer, browserleaks WebRTC, pixelscan, liarjs), when auditing what a vendor runtime does with API and proxy credentials, or when asking which layers browser isolation cannot cover at all. Also for 'profile isolation check', 'fingerprint consistency test', 'timezone mismatch', 'WebRTC leak', 'canvas hash unstable', 'account association', 'temporary profile', '防关联', '多账号', '隔离自检'. The SDK is anti-detect-browser; MCP is browser-mcp-agent.
- multi-account-scrapingantibrow
Run the same scrape or task across many accounts at once - each in its own browser profile with its own fingerprint, cookies and exit IP - and read data from sites that need a session or that answer a plain HTTP scraper with a captcha while answering a real browser. One command per site returns JSON, so there are no selectors to write or repair: Amazon and Walmart search, Google and DuckDuckGo results, Reddit posts and comments, X timeline, Medium, Yelp, Indeed job listings, Hacker News, GitHub, PyPI, npm, plus exit-IP and fingerprint checks. Use for multi-account operations you are authorized to run, price and listing monitoring per region, SERP collection, logged-in data, and scrapers that keep breaking. Also for 'scrape amazon', 'google search results', 'reddit data', 'scrape logged in site', 'run task on many accounts', 'site blocks my scraper', 'scraping without selectors'. Node or Python.
Create, modify, debug, and deploy Apify Actors, and write their input and output schemas. Use when building an Actor from scratch, changing or troubleshooting Actor code, generating or updating .actor schema files, or pushing an Actor to the Apify platform. To wrap an existing non-Actor project, use apify-actorization instead.
apify-actorizationapifyConvert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Use when migrating code to Apify, wrapping CLI tools as Actors, or adding Actor SDK to existing projects.
Deprecated. Output schema generation moved to the apify-actor-development skill; prefer that skill whenever it is available.
Design and build an official Apify integration for a company's product - workflow-automation apps (Zapier/n8n-style), AI agent plugins (coding-agent skills+MCP bundles or OpenClaw/Hermes-style harnesses), AI framework packages (LangChain/LlamaIndex-style), or direct application clients via apify-client. Use when planning, creating, or reviewing an integration that exposes Apify Actors, runs, datasets, or key-value stores inside another product.
Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, LinkedIn, X/Twitter, Google Maps, Google Search, Google Trends, Reddit, Airbnb, Yelp, and 15+ more platforms. Use for lead generation, brand monitoring, competitor analysis, influencer discovery, trend research, content analytics, audience analysis, review analysis, SEO intelligence, recruitment, or any data extraction task.
apollo-clientapollographqlGuide for building React applications with Apollo Client 4.x. Use this skill when: (1) setting up Apollo Client in a React project, (2) writing GraphQL queries or mutations with hooks, (3) configuring caching or cache policies, (4) managing local state with reactive variables, (5) troubleshooting Apollo Client errors or performance issues.
- apollo-connectorsapollographql
DEPRECATED: superseded by the graphos-factory skill (npx skills add apollographql/skills@graphos-factory), which builds and maintains a Connectors subgraph from a REST API with recorded decisions and verification. Guide for integrating REST APIs into GraphQL supergraphs using Apollo Connectors with @source and @connect directives. Use this skill when the user: (1) mentions "connectors", "Apollo Connectors", or "REST Connector", (2) wants to integrate a REST API into GraphQL, (3) references @source or @connect directives, (4) works with files containing "# Note to AI Friends: This is an Apollo Connectors schema".
- apollo-federationapollographql
Guide for authoring Apollo Federation subgraph schemas. Use this skill when: (1) creating new subgraph schemas for a federated supergraph, (2) defining or modifying entities with @key, (3) sharing types/fields across subgraphs with @shareable, (4) working with federation directives (@external, @requires, @provides, @override, @inaccessible), (5) troubleshooting composition errors, (6) any task involving federation schema design patterns.
- apollo-iosapollographql
Guide for building Apple-platform applications with Apollo iOS, the strongly-typed GraphQL client for Swift. Use this skill when: (1) adding Apollo iOS to a Swift Package Manager or Xcode project, (2) configuring `apollo-codegen-config.json` and running code generation, (3) configuring an `ApolloClient` with auth, interceptors, and caching, (4) writing queries, mutations, or subscriptions from SwiftUI views, (5) writing tests against generated operation mocks.
- apollo-kotlinapollographql
Guide for building applications with Apollo Kotlin, the GraphQL client library for Android and Kotlin. Use this skill when: (1) setting up Apollo Kotlin in a Gradle project for Android, Kotlin/JVM, or KMP, (2) configuring schema download and codegen for GraphQL services, (3) configuring an `ApolloClient` with auth, interceptors, and caching, (4) writing queries, mutations, or subscriptions,
- apollo-mcp-serverapollographql
Guide for using Apollo MCP Server to connect AI agents with GraphQL APIs. Use this skill when: (1) setting up or configuring Apollo MCP Server, (2) defining MCP tools from GraphQL operations, (3) using introspection tools (introspect, search, validate, execute, explorer), (4) configuring authentication, CORS, health checks, or telemetry, (5) writing Rhai scripts for request lifecycle hooks, (6) defining MCP prompts, (7) troubleshooting MCP server connectivity or tool execution issues.
- apollo-routerapollographql
Version-aware guide for configuring and running Apollo Router for federated GraphQL supergraphs. Generates correct YAML for both Router v1.x and v2.x. Use this skill when: (1) setting up Apollo Router to run a supergraph, (2) configuring routing, headers, or CORS, (3) implementing custom plugins (Rhai scripts or coprocessors), (4) configuring telemetry (tracing, metrics, logging), (5) troubleshooting Router performance or connectivity issues, (6) securing the graph with JWT, declarative field-level authorization directives, or persisted-query safelisting, (7) managing router.yaml as version-controlled config with CI/CD validation.
- apollo-router-plugin-creatorapollographql
Guide for writing Apollo Router native Rust plugins. Use this skill when: (1) users want to create a new router plugin, (2) users want to add service hooks (router_service, supergraph_service, execution_service, subgraph_service), (3) users want to modify an existing router plugin, (4) users need to understand router plugin patterns or the request lifecycle. (5) triggers on requests like "create a new plugin", "add a router plugin", "modify the X plugin", or "add subgraph_service hook".
- apollo-serverapollographql
Guide for building GraphQL servers with Apollo Server 5.x. Use this skill when: (1) setting up a new Apollo Server project, (2) writing resolvers or defining GraphQL schemas, (3) implementing authentication or authorization, (4) creating plugins or custom data sources, (5) troubleshooting Apollo Server errors or performance issues.
- graphos-factoryapollographql
Build and iterate on an Apollo Connectors subgraph for a GraphOS supergraph from a REST API, with or without an OpenAPI or Swagger spec, in a dedicated git workspace that records what the API offers, the user's operation and field selection, every design decision, and the evidence each verification layer produced. Use whenever the user wants to wrap a REST API as a GraphQL subgraph for their supergraph, add or remove operations or fields from an existing connector subgraph, refresh one against a new spec, or record live API traffic as test fixtures, even if they do not say "connector", "subgraph" or "Apollo".
- graphql-operationsapollographql
Guide for writing GraphQL operations (queries, mutations, fragments) following best practices. Use this skill when: (1) writing GraphQL queries or mutations, (2) organizing operations with fragments, (3) optimizing data fetching patterns, (4) setting up type generation or linting, (5) reviewing operations for efficiency.
- graphql-schemaapollographql
Guide for designing and changing GraphQL schemas following industry best practices. Use this skill whenever you create or edit GraphQL SDL, such as a `schema.graphql` file or `typeDefs`, including when: (1) designing a new GraphQL schema or API, (2) adding or changing types, fields, arguments, mutations, or descriptions in an existing schema, (3) reviewing existing schema for improvements, (4) deciding on type structures or nullability, (5) implementing pagination or error patterns, (6) ensuring security in schema design.
- roverapollographql
Guide for using Apollo Rover CLI to manage GraphQL schemas and federation. Use this skill when: (1) publishing or fetching subgraph/graph schemas, (2) composing supergraph schemas locally or via GraphOS, (3) running local supergraph development with rover dev, (4) validating schemas with check and lint commands, (5) configuring Rover authentication and environment, (6) exploring or searching a graph's schema for agent-driven discovery (rover schema describe / rover schema search), (7) initializing a new graph project or MCP server with rover init, (8) working with Apollo Connectors, contracts, persisted queries, or client operations, (9) managing API keys, plugins, templates, or graph artifacts.
- rust-best-practicesapollographql
Guide for writing idiomatic Rust code based on Apollo GraphQL's best practices handbook. Use this skill when: (1) writing new Rust code or functions, (2) reviewing or refactoring existing Rust code, (3) deciding between borrowing vs cloning or ownership patterns, (4) implementing error handling with Result types, (5) optimizing Rust code for performance, (6) writing tests or documentation for Rust projects.
- skill-creatorapollographql
Guide for creating effective skills for Apollo GraphQL and GraphQL development. Use this skill when: (1) users want to create a new skill, (2) users want to update an existing skill, (3) users ask about skill structure or best practices, (4) users need help writing SKILL.md files.
forge-app-builderatlassianPlan, build, scaffold, or safely extend Atlassian Forge apps using current official documentation. Use for fresh Forge apps, existing-app feature work, module and manifest changes, UI Kit or Custom UI implementation, backend functions and events, Atlassian or external APIs, storage, permissions, environment configuration, distribution-affecting implementation, validation, and explicitly authorized deployment or installation; route standalone debugging and specialist reviews to their dedicated skills.
- forge-app-reviewatlassian
Performs a lightweight pre-release readiness review of Atlassian Forge apps across manifest/module wiring, architecture, runtime compatibility, dependency posture, tests, deploy readiness, and obvious security, cost, or reliability smells. Use when the user asks "review my Forge app", "pre-deploy check", "is this app ready to ship", "review manifest", "general app review", "release readiness", or asks for a broad quality pass. Do not use for deep security audits/SAST/exploitability review, cost optimization, or diagnosing a known broken app; route those to forge-security-review, forge-cost-optimizer, or forge-debugger respectively.
- forge-connectoratlassian
Guides building and deploying Atlassian Forge Teamwork Graph connector apps that ingest external data into Atlassian's Teamwork Graph, making it searchable in Rovo Search and surfaced in Rovo Chat. Use when the user wants to build a Forge connector, ingest external data into Atlassian, connect a third-party tool (e.g. Google Drive, ServiceNow, Salesforce) to Atlassian, make external content searchable in Rovo, build a graph:connector module, use the @forge/teamwork-graph SDK, or implement onConnectionChange / validateConnection functions.
- forge-cost-optimizeratlassian
Optimizes Atlassian Forge apps to reduce platform consumption and avoid unnecessary costs using Atlassian's "Optimise Forge platform costs" guidance. Use when the user asks to optimize Forge app costs, reduce Forge invocations, lower GB-seconds, reduce storage or log usage, tune memory, replace polling, improve scheduled triggers, reduce KVS writes, move work to the frontend, use bridge APIs, batch API calls, add caching, or evaluate Forge Remote trade-offs. By default, perform an audit first and offer to make the recommended changes after presenting the audit. Only modify files immediately when the user explicitly asks the agent to implement or apply optimizations.
- forge-debuggeratlassian
Diagnoses and fixes issues in Atlassian Forge apps. Use this skill whenever a Forge app has errors, crashes, shows blank UI, fails to deploy, doesn't appear after installation, has permission issues, or produces unexpected output. Trigger on any mention of forge logs, forge deploy errors, resolver errors, blank panels, missing scopes, Custom UI not rendering, production vs dev discrepancies, or any Jira/Confluence app that "stopped working". Also trigger when the user asks to debug, troubleshoot, investigate, or fix a Forge app issue — even if they haven't used the word "Forge" but describe a Jira panel or Confluence macro acting up.
- forge-onboardingatlassian
Guide a first-time Forge builder through building Forge Guru, a Rovo Agent that answers Forge questions. Use for Forge onboarding, a first Forge or Rovo app, or resuming this tutorial. Route unrelated existing-app changes, debugging, reviews, and connector work to the specialist skills.
- forge-security-reviewatlassian
Performs a white-box security review of Atlassian Forge apps using structured, Forge-specific security rules and evidence-driven reporting. Use when the user asks for a Forge security review, security audit, vuln assessment, pentest-style code review, authz review, tenant isolation analysis, web trigger hardening, or static analysis execution for a Forge app.
auth0auth0Use when adding, fixing, or improving how an app authenticates users or protects an API, or when using or configuring any Auth0 feature — signing users in and out, sessions and tokens, guarding routes and endpoints, MFA, passwordless passkey login (WebAuthn), SSO, Organizations, RBAC, custom domains, Universal Portals for hosted account and organization self-service, or Universal Login branding. Also use to audit a tenant's health, security, and plan fit (CheckMate), to debug why an auth flow fails, to migrate from another auth provider, or to set up the Vercel native integration. Covers any web, mobile, or backend framework and every Auth0 SDK, tool, and API. Use even if the user never mentions Auth0.
funnel-platform-pickerautonnelChoose a landing page or sales funnel platform by working out the real total cost and lock-in for a specific case - comparing ClickFunnels, CartFlows, FunnelKit, systeme.io, GoHighLevel, Shopify apps, hand-rolled pages and self-hosted open-source options. Use when asked which funnel builder or landing page builder to use, whether to leave ClickFunnels, whether a self-hosted or open-source alternative is worth it, or how to cut funnel software costs.
- landing-page-conversion-auditautonnel
Audit a landing page, sales page or checkout page for conversion leaks and return a fix list ordered by expected revenue impact. Use when asked to review, critique or improve a landing page, sales page, opt-in page, product page or checkout flow, when conversion rate is low, when paid traffic is not converting, or when someone asks "why isn't this page converting" or wants a CRO / landing page review.
- post-purchase-upsell-flowautonnel
Design and implement one-click post-purchase upsells and downsells that raise average order value without hurting the main conversion rate. Use when asked to increase AOV, add an upsell, cross-sell or downsell after checkout, build a one-click upsell flow, monetize the thank-you page, or when someone asks how to make more revenue per customer from the same ad spend.
- sales-funnel-blueprintautonnel
Turn an offer into a concrete multi-step sales funnel spec - page-by-page structure, price ladder, copy outline and the metrics each step must hit. Use when asked to build a sales funnel, marketing funnel, landing page flow, lead magnet funnel, webinar funnel, tripwire or VSL funnel, when planning a product launch page flow, or when someone asks "what pages do I need" for selling something online.
- self-hosted-funnel-launchautonnel
Deploy a self-hosted funnel builder, take a funnel from empty install to published - landing page, checkout, one-click upsell, thank-you - and drive it from an agent over MCP. Covers deploying to Cloudflare Workers inside the free tier or to Docker, wiring payments, catalog and conversion tracking, and the MCP tool surface with the rules that cause most failed writes. Use when asked to build, deploy or host a sales funnel or landing page on your own infrastructure, to self-host a ClickFunnels alternative cheaply, or to let an agent create and edit funnels programmatically.
- server-side-conversion-trackingautonnel
Set up server-side conversion tracking so purchases are reported accurately to Facebook, TikTok, Google and Bing despite iOS restrictions, ad blockers and cookie loss. Use when conversions are under-reported, when platform-reported purchases do not match real orders, when asked about Conversions API / Events API / offline conversions / CAPI, click id passthrough (fbclid, ttclid, gclid, msclkid), or when ad optimization has degraded after tracking changes.
axiom-alertingaxiomhqCreate and manage Axiom monitors and notifiers via the v2 public API. Use when building alerting, routing notifications, validating monitor behavior, and maintaining alert configurations end-to-end.
- axiom-building-dashboardsaxiomhq
Designs and builds Axiom dashboards via API. Covers chart types, APL and metrics/MPL query patterns, SmartFilters, layout, and configuration options. Use when creating dashboards, migrating from Splunk, or configuring chart options.
- axiom-controlling-costsaxiomhq
Analyzes Axiom query patterns to find unused data, then builds dashboards and monitors for cost optimization. Use when asked to reduce Axiom costs, find unused columns or field values, identify data waste, or track ingest spend.
- axiom-metrics-chartaxiomhq
Render saved Axiom metrics v2 or v3 JSON as line charts in a terminal or transcript. Uses Unicode/ASCII by default and supports PNG/SVG/sixel with gnuplot. Use when plotting metrics query results.
- axiom-spl-to-aplaxiomhq
Translates Splunk SPL queries to Axiom APL. Provides command mappings, function equivalents, and syntax transformations. Use when migrating from Splunk, converting SPL queries, or learning APL equivalents of SPL patterns.
- axiom-sreaxiomhq
Expert SRE investigator for incidents and debugging. Uses hypothesis-driven methodology and systematic triage. Can query Axiom observability when available. Use for incident response, root cause analysis, production debugging, or log investigation.
- building-dashboardsaxiomhq
Designs and builds Axiom dashboards via API. Covers chart types, APL and metrics/MPL query patterns, SmartFilters, layout, and configuration options. Use when creating dashboards, migrating from Splunk, or configuring chart options.
- controlling-costsaxiomhq
Analyzes Axiom query patterns to find unused data, then builds dashboards and monitors for cost optimization. Use when asked to reduce Axiom costs, find unused columns or field values, identify data waste, or track ingest spend.
- metrics-chartaxiomhq
Render saved Axiom metrics v2 or v3 JSON as line charts in a terminal or transcript. Uses Unicode/ASCII by default and supports PNG/SVG/sixel with gnuplot. Use when plotting metrics query results.
- query-metricsaxiomhq
Runs metrics queries against Axiom MetricsDB via scripts. Discovers available metrics, tags, and tag values. Use when asked to query metrics, explore metric datasets, check metric values, or investigate OTel metrics data.
- spl-to-aplaxiomhq
Translates Splunk SPL queries to Axiom APL. Provides command mappings, function equivalents, and syntax transformations. Use when migrating from Splunk, converting SPL queries, or learning APL equivalents of SPL patterns.
- writing-evalsaxiomhq
Scaffolds evaluation suites for the Axiom AI SDK. Generates eval files, scorers, flag schemas, and config from natural-language descriptions. Use when creating evals, writing scorers, setting up flag schemas, or configuring axiom.config.ts.
base-mcpbaseBase MCP — gives your AI assistant access to a Base Account via the Base MCP server (wallet-mcp.coinbase.com). Wallet, portfolio, sending, swapping, signing, x402 payments, batched contract calls, and transaction history across supported chains.
- build-on-basebase
Complete Base development playbook. Covers: (1) Network — Base RPC URLs, chain IDs (8453/84532), explorer config, testnet setup, connect to Base, Base Sepolia; (2) Contracts — Foundry deployment, forge create, BaseScan verification, CDP faucet, testnet ETH, deploy contract to Base; (3) Builder Codes — ERC-8021 attribution suffix, referral fees, dataSuffix for Wagmi/Viem/Privy/ ethers.js/window.ethereum, transaction attribution, earn referral fees, append builder code; (4) Agent registration — trading bots, AI agents, automated senders, ERC-8021 attribution wiring, base.dev API, register agent, builder code registration; (5) Node operation — run Base node, Reth setup, hardware requirements, self-hosted RPC, sync.
- plugin-reviewbase
Validate and review Wallet MCP plugin files against the Plugin Specification. Use when writing a new plugin, preparing a plugin PR for submission, self-checking a plugin before opening a PR, or reviewing someone else's plugin PR. Triggers on requests like "check my plugin against the spec", "validate this plugin file", "review my plugin PR", "does this plugin conform to the spec", "prepare my plugin for submission", "write a plugin for X protocol".
- skill-creatorbase
Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
- vibenetbase
Build on vibenet — Base's devnet for native account abstraction (EIP-8130), payer gas sponsorship (ERC-8168), and Cobalt 200ms native blocks. Use whenever the user mentions vibenet, EIP-8130, ERC-8168, 8130 accounts, native account abstraction, session keys, actors, policies, payers, gas sponsorship on Base, 200ms blocks, Cobalt, BaseTime, timestampMs / blockTimestampMs, sub-second or millisecond block timestamps, migrating from Flashblocks, or newHeads / WebSocket streaming on vibenet — or is writing code that creates or operates 8130 smart accounts, authorizes session-key actors, sends batched calls, sponsors gas with a payer, queries or streams vibenet blocks, times a transaction's inclusion, or wires a frontend/script against the vibenet devnet or Base Sepolia.
- wallet-mcpbase
Wallet MCP — gives your AI assistant access to a Coinbase Wallet Account via the Wallet MCP server (wallet-mcp.coinbase.com). Wallet, portfolio, sending, swapping, signing, x402 payments, batched contract calls, and transaction history across Base, Ethereum, Arbitrum, Optimism, Polygon, BNB Chain, Avalanche, and Robinhood Chain.
better-auth-best-practicesbetter-authConfigure Better Auth server and client, set up database adapters, manage sessions, add plugins, and handle environment variables. Use when users mention Better Auth, betterauth, auth.ts, or need to set up TypeScript authentication with email/password, OAuth, or plugin configuration.
- better-auth-security-best-practicesbetter-auth
Configure rate limiting, manage auth secrets, set up CSRF protection, define trusted origins, secure sessions and cookies, encrypt OAuth tokens, track IP addresses, and implement audit logging for Better Auth. Use when users need to secure their auth setup, prevent brute force attacks, or harden a Better Auth deployment.
- create-authbetter-auth
Scaffold and implement authentication in TypeScript/JavaScript apps using Better Auth. Detect frameworks, configure database adapters, set up route handlers, add OAuth providers, and create auth UI pages. Use when users want to add login, sign-up, or authentication to a new or existing project with Better Auth.
- email-and-password-best-practicesbetter-auth
Configure email verification, implement password reset flows, set password policies, and customise hashing algorithms for Better Auth email/password authentication. Use when users need to set up login, sign-in, sign-up, credential authentication, or password security with Better Auth.
- organization-best-practicesbetter-auth
Configure multi-tenant organizations, manage members and invitations, define custom roles and permissions, set up teams, and implement RBAC using Better Auth's organization plugin. Use when users need org setup, team management, member roles, access control, or the Better Auth organization plugin.
- two-factor-authentication-best-practicesbetter-auth
Configure TOTP authenticator apps, send OTP codes via email/SMS, manage backup codes, handle trusted devices, and implement 2FA sign-in flows using Better Auth's twoFactor plugin. Use when users need MFA, multi-factor authentication, authenticator setup, or login security with Better Auth.
boxboxFoundation skill for working with Box. Use this whenever the user mentions Box — authentication and MCP/CLI setup, choosing between MCP/CLI/REST, rate-limit and pacing guidance, troubleshooting Box errors (401/403/404/409/429), or working with Box MCP tools (files, search, collaboration, AI, hubs, doc gen). Route general Box requests to the right reference. For explicit CLI requests, use box-cli when installed.
- box-clibox
Use the official Box CLI for Box command-line operations, reproducible shell automation, CLI authentication or troubleshooting, and bulk Box work. Do not use for generic shell questions, Box strategy, or application code that should use a Box SDK.
- box-integration-best-practicesbox
Build, debug, or review repeatable Box API integrations and agent workflows for efficient calls, bulk work, and 429 handling.
Shared building blocks for Box-based legal workflows — Box collaboration role definitions, Box AI usage boundaries (what AI must not decide), and reusable human-in-the-loop confirmation phrasings. Referenced by box-legal-workflows-ma, box-legal-workflows-intake, and box-legal-workflows-contract skills.
Automate contract review and monitoring with Box MCP — find new or expiring contracts, compare them against firm templates to flag material variances, write structured contract metadata back to Box for searchability, and produce variance reports with citations. Use this skill when the user mentions contract review or monitoring, NDA or MSA review, contract expiration or renewals, contract metadata, or variance analysis, even if they don't name a specific Box tool.
Automate legal client intake and onboarding with Box MCP — review intake documents for completeness against firm requirements, summarize risk for attorney review, route incomplete or high-risk submissions to the right attorney, extract client and matter metadata to Box, and generate engagement letters from Box DocGen templates. Use this skill when the user mentions client intake, client onboarding, new client review, intake documents, or engagement letters.
Build and manage M&A virtual data rooms with Box MCP — create secure due-diligence folder structures, scope role-based access for internal teams and external parties, validate permissions before sharing, and answer cross-document due-diligence questions with Box AI. Use this skill when the user mentions M&A, deal rooms, data rooms, VDRs, due diligence, or mergers and acquisitions.
- box-mcpbox
Connect clients to Box's hosted MCP server and operate Box through its tools. Use for Box MCP setup, authentication, missing tools, or Box tasks using an MCP connection.
- box-sdk-developmentbox
Build or debug application code using an official Box SDK, especially Python or TypeScript/Node. Covers SDK call correctness, file transfer, bulk work, rate limits, and observability; not one-off CLI or MCP content operations.
example-skillbradautomatesExample skill that confirms the marketplace is wired correctly. Triggers when the user says "test the marketplace", "verify marketplace install", or asks for a marketplace smoke test. Replace or delete once you have your own skills.
- marketplace-managerbradautomates
Owner-only tooling for managing a private skills marketplace that serves both Claude Code and Codex CLI from the same repo. Use when the user says "set up the marketplace", "init the marketplace", "add a skill to the team marketplace", "import this skill into the marketplace", "publish to the marketplace", "ship it", "add a plugin to the marketplace", "check marketplace status", "what's in the marketplace", "list skills", "what have I shipped", "rename the marketplace", or otherwise wants to administer their team's shared skills repo. Handles first-run init, importing existing skills from anywhere on disk (~/.claude/skills, ~/.codex/skills, project dirs), scaffolding new plugins, publishing (commit + push), and reporting status. Writes parallel manifests for both Claude Code (.claude-plugin/) and Codex (.agents/, .codex-plugin/) in lockstep. Not for authoring skills from scratch — use the built-in skill-creator / write-a-skill skill for that, then import the result here.
answersbraveUSE FOR AI-grounded answers via OpenAI-compatible /chat/completions. Two modes: single-search (fast) or deep research (enable_research=true, thorough multi-search). Streaming/blocking. Citations.
- bxbrave
USE FOR web search, research, RAG, grounding, browse, find, lookups, fact-checking, documentation, agentic AI. All-in-one, optimized for AI agents. Pre-extracted, token-budgeted web content, deep research, news, images, videos, places, custom ranking
- bx-searchbrave
Web search using the Brave Search CLI (`bx`). Use for ALL web search requests — including "search for", "look up", "find", "what is", "how do I", "google this", and any request needing current or external information. Prefer this over the built-in web_search tool whenever bx is available. Also use for: documentation lookup, troubleshooting research, RAG grounding, news, images, videos, local places, and AI-synthesized answers.
- images-searchbrave
USE FOR image search. Returns images with title, source URL, thumbnail. Supports SafeSearch filter. Up to 200 results.
- llm-contextbrave
USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.
- local-descriptionsbrave
USE FOR getting AI-generated POI text descriptions. Requires POI IDs from local-place-search, or from web-search with result_filter=locations. Returns markdown descriptions grounded in web search context. Max 20 IDs per request.
- local-place-searchbrave
USE FOR finding places in the physical world - businesses, POIs, street addresses, cities and streets. Results carry address, coordinates, rating, opening hours and phone, so basic details need no follow-up call. Standalone - no POI IDs or prior web search required; the IDs it returns work with local-pois and local-descriptions. Locate by coordinates or a location string, or omit both to search globally. Omit the query to browse an area. Max 100 results.
- local-poisbrave
USE FOR getting local business/POI details. Requires POI IDs from local-place-search, or from web-search with result_filter=locations. Returns full business information including ratings, hours, contact info. Max 20 IDs.
- news-searchbrave
USE FOR news search. Returns news articles with title, URL, description, age, thumbnail, profile. Supports freshness and date range filtering, SafeSearch filter and Goggles for custom ranking.
- spellcheckbrave
USE FOR spell correction. Returns corrected query if misspelled. Most search endpoints have spellcheck built-in; use this only for pre-search query cleanup or "Did you mean?" UI.
- suggestbrave
USE FOR query autocomplete/suggestions. Fast (<100ms). Returns suggested queries as user types. Supports rich suggestions with entity info. Typo-resilient.
- videos-searchbrave
USE FOR video search. Returns videos with title, URL, thumbnail, duration, view count, creator. Supports freshness filters, SafeSearch, pagination.
- web-searchbrave
USE FOR web search. Returns ranked results with snippets, URLs, thumbnails. Supports freshness filters, SafeSearch, Goggles for custom ranking, pagination. Primary search endpoint.
1688-product-detailbrowser-actExtracts comprehensive wholesale product data from 1688.com product detail pages: title, tiered pricing, SKU variants with dimensions/weight, product images, seller info, shop scores, buyer protection, cross-border flags, product attributes, coupon/promotion data, and review stats. Use when user mentions 1688, 1688.com, wholesale China, alibaba wholesale, B2B China sourcing, Chinese wholesale scraper, 1688 product scrape, 1688 offer, 1688 detail, extract 1688 data, pull 1688 listings, get wholesale price, 1688 supplier info, factory stats 1688, 1688 SKU variants, 1688 product attributes, 1688 shop score, DSR score 1688, 1688 buyer protection, 1688 cross-border, 1688 dropship. Also applies to: scraping bulk product data from 1688 by offer ID list, monitoring 1688 supplier metrics, extracting 1688 pricing tiers for resale analysis.
- airbnb-listing-detailbrowser-act
Fetches complete Airbnb listing details for a given numeric listing ID via the internal GraphQL API, returning title, room type, description, amenities, photos, coordinates, city, house rules, highlights, ratings, review count, bedroom configuration, and property overview. Use when user mentions Airbnb listing details, Airbnb property info, Airbnb room details, get Airbnb listing data, Airbnb amenities list, Airbnb house rules, Airbnb property description, Airbnb detail page scraper, Airbnb rooms detail, Airbnb property page data, Airbnb listing info, fetch Airbnb room details, pull Airbnb listing.
- airbnb-search-listingbrowser-act
Extracts Airbnb accommodation search results from a destination query via SSR-embedded data, returning listing ID, URL, name, coordinates, rating, price, photos, and badge info for each result, plus pagination cursors for multi-page retrieval. Use when user mentions Airbnb search results, Airbnb listings, vacation rental search, short-term rental listings, scrape Airbnb, get Airbnb data, find rentals on Airbnb, Airbnb destination search, Airbnb property list, Airbnb stays search, Airbnb accommodation results, pull Airbnb listings, collect Airbnb search data, Airbnb scraper, Airbnb search page extraction, Airbnb search by destination.
- amazon-alexa-qabrowser-act
Amazon Alexa for Shopping Q&A automation: submits questions to Amazon's Alexa/Rufus AI shopping assistant and collects response text; supports optional keyword search context (navigate to search results page before asking for category-specific answers). Use when user mentions Amazon Alexa, Rufus, Amazon shopping assistant, Amazon AI chat, ask Amazon, Amazon Q&A, automate Alexa questions, Rufus chatbot, Amazon assistant automation, collect Alexa responses, bulk question submission to Amazon, keyword search context, category research. Also applies to extracting Amazon product recommendations from conversational AI, automating repeated queries to Amazon's AI shopping feature, collecting Alexa shopping responses at scale, or market research within a specific product category.
- amazon-asin-lookup-api-skillbrowser-act
This skill helps users extract structured product details from Amazon using a specific ASIN (Amazon Standard Identification Number). Use this skill when the user asks to get Amazon product details by ASIN, lookup Amazon product title and price using ASIN, extract Amazon product ratings and reviews count for a specific ASIN, check Amazon product availability and current price, get Amazon product description and features via ASIN, enrich product catalog with Amazon data using ASIN, monitor Amazon product price changes for specific ASINs, retrieve Amazon product brand and material information, fetch Amazon product images and specifications by ASIN, validate Amazon ASIN and get product metadata.
This skill helps users extract structured best-selling product data from Amazon via the BrowserAct API. Agent should proactively apply this skill when users express needs like search for best selling products on Amazon, extract Amazon product data based on keywords, find top rated Amazon products, monitor Amazon competitor prices and sales, discover trending products on Amazon marketplace, extract Amazon product titles prices and ratings, gather Amazon product sales volume for market research, search Amazon best sellers in specific region, collect Amazon product reviews and promotion details, analyze Amazon product availability and badges, get Amazon product data for market analysis.
- amazon-bestseller-listingbrowser-act
Amazon Best Sellers listing scraper: extract product cards from any Amazon Best Sellers (zgbs) or /gp/bestsellers/ category page — returns rank (position on chart), asin, title, url, image, imageAlt, price, stars, reviewCount, ratingRaw per item, plus category metadata (categoryName, categoryFullName, categoryUrl) and pagination state (currentPage, hasNextPage, nextPageUrl). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, etc.). Use when user mentions Amazon Best Sellers, Amazon bestsellers, Amazon top 100, Amazon zgbs, Amazon /zgbs/, Amazon /gp/bestsellers/, Amazon Best Sellers Rank, Amazon BSR, Amazon top ranked products, Amazon top-selling products, Amazon chart, Amazon category ranking, Amazon best sellers by category, Amazon best sellers electronics, Amazon best sellers kitchen, Amazon best sellers toys, scrape Amazon bestsellers, extract Amazon top 100, Amazon rank scraper, Amazon best seller list, Amazon leaderboard, Amazon trending products, discover trending Amazon products, Amazon niche discovery, Amazon top ranked ASINs. Also applies to competitive intelligence via ranking snapshots, spotting up-and-coming products, sourcing bestseller ASINs for further enrichment, tracking rank changes over time, and building bestseller-per-category datasets.
- amazon-buy-box-monitor-api-skillbrowser-act
This skill helps users extract basic product details other sellers prices and seller ratings from Amazon via ASIN automatically using the BrowserAct API. Agent should proactively apply this skill when users express needs like query Amazon buy box information, monitor Amazon product prices, extract Amazon product details by ASIN, check other sellers prices on Amazon, get Amazon seller ratings and feedback count, monitor buy box ownership for a specific ASIN, track Amazon fulfillment methods for competitors, compare Amazon product prices across different sellers, retrieve Amazon buy box availability status, analyze Amazon seller profile details.
- amazon-competitor-analyzerbrowser-act
Scrapes Amazon product data from ASINs using browseract.com automation API and performs surgical competitive analysis. Compares specifications, pricing, review quality, and visual strategies to identify competitor moats and vulnerabilities.
- amazon-listing-competitor-analysis-skillbrowser-act
This skill helps users analyze Amazon competitor listings by ASIN and produce structured competitive intelligence plus strategic opportunity points for their own go-to-market. The Agent should proactively apply this skill when users want to analyze a competitor Amazon listing by ASIN, understand what a top-ranked product does right in content keywords or visuals, find market gaps and unmet buyer needs, turn competitor research into opportunity maps for their brand, identify keyword placement patterns on rival listings, extract SEO insights from Amazon product pages, reverse-engineer competitor bullet and title strategies, mine competitor reviews for buyer psychology, compare seller and A plus content patterns, run gap analysis before launching a new SKU, research why a listing wins conversion signals, synthesize whitespace you can own versus the diagnosed listing, or say just look at this ASIN with a competitive or optimization angle.
- amazon-product-api-skillbrowser-act
This skill helps users extract structured product listings from Amazon, including titles, ASINs, prices, ratings, and specifications. Use this skill when users want to search for products on Amazon, find the best selling brand products, track price changes for items, get a list of categories with high ratings, compare different brand products on Amazon, extract Amazon product data for market research, look for products in a specific language or marketplace, analyze competitor pricing for keywords, find featured products for search terms, get technical specifications like material or color for product lists.
- amazon-product-detailbrowser-act
Amazon product detail page scraper: extract full product data from any open Amazon product detail URL (any /dp/{asin} or /gp/product/{asin} page across all Amazon regional TLDs) — returns asin, url, title, brand, price, listPrice, stars, reviewsCount, starsBreakdown (5/4/3/2/1 star percentages), answeredQuestions, inStock, inStockText, delivery, fastestDelivery, returnPolicy, breadCrumbs, features (bullet points), description, bookDescription, thumbnailImage, highResolutionImages, galleryThumbnails, productOverview (Brand/Model/etc.), attributes (tech spec table), attributesMapped (flat key-value), bestsellerRanks (rank + category + url), variantAttributes (currently selected color/size/style), variantAsins, seller (name + id + url), isAmazonChoice, amazonChoiceText, monthlyPurchaseVolume, hasAPlusContent, hasBrandStory, aiReviewsSummary, reviewsLink, productPageReviews (sample), videosCount, locationText, loadedCountryCode. Works on amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.fr, amazon.it, amazon.es, amazon.ca, amazon.com.au, amazon.in, amazon.com.mx, amazon.com.br, amazon.nl, amazon.se, amazon.sg, amazon.ae, amazon.sa, amazon.pl, amazon.tr, amazon.eg. Use when user mentions Amazon product page, Amazon /dp/, Amazon dp URL, Amazon ASIN scraper, Amazon product detail, Amazon PDP, Amazon product data, Amazon product info, Amazon product fields, Amazon product attributes, Amazon full field extraction, Amazon per-ASIN enrichment, Amazon rating breakdown, Amazon stars breakdown, Amazon bestseller rank, Amazon BSR, Amazon variants, Amazon variant ASINs, Amazon color size options, Amazon feature bullets, Amazon A+ content, Amazon brand story, Amazon AI review summary, Amazon bought in past month, Amazon monthly sales volume, Amazon Amazon's Choice badge, Amazon seller info, scrape Amazon product, enrich Amazon ASIN, Amazon ASIN details, Amazon product review data. Also applies to bulk ASIN enrichment from a list of URLs, competitive product research, brand catalog audits, price and stock monitoring per ASIN, and building a normalized product dataset from a list of Amazon URLs.
- amazon-product-search-api-skillbrowser-act
This skill is designed to help users automatically extract product data from Amazon search results. The Agent should proactively apply this skill when users request searching for products related to keywords, finding best-selling items from specific brands, monitoring product prices and availability on Amazon, extracting product listings for market research, collecting product ratings and review counts for competitive analysis, finding specific products with a maximum count, searching Amazon in different languages for localized results, tracking monthly sales estimates for brand products, gathering product URLs and titles for a product catalog, scanning Amazon for Best Seller tags in a specific category, monitoring shipping and delivery information for brand items, building a structured dataset of Amazon search results.
- amazon-reviews-api-skillbrowser-act
This skill helps users automatically extract Amazon product reviews via the Amazon Reviews API. Agent should proactively apply this skill when users express needs like getting reviews for Amazon product with ASIN B07TS6R1SF, analyzing customer feedback for a specific Amazon item, getting ratings and comments for a competitive product, tracking sentiment of recent Amazon reviews, extracting verified purchase reviews for quality assessment, summarizing user experiences from Amazon product pages, monitoring product performance through customer reviews, collecting reviewer profiles and links for market research, gathering review titles and descriptions for content analysis, scraping Amazon reviews without requiring a login.
- amazon-search-listingbrowser-act
Amazon search and category listing scraper: extract product listings from any Amazon search results page, keyword search URL, or category browse page and return per-item cards (asin, title, url, image, price, listPrice, stars, reviewCount, badges, isAmazonChoice, isBestSeller, isSponsored, delivery, boughtInPast, positionIndex) plus pagination state (currentPage, hasNextPage, nextPageUrl, totalResultsApprox). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.in, amazon.fr, amazon.ca, amazon.com.au, amazon.it, amazon.es, amazon.com.mx, amazon.com.br, amazon.nl, amazon.se, amazon.sg, amazon.ae, amazon.sa, amazon.pl, amazon.tr, amazon.eg). Use when user mentions Amazon, amazon.com, Amazon SERP, Amazon search results, Amazon keyword search, Amazon category page, Amazon subcategory URL, scrape Amazon listings, extract Amazon search, Amazon product cards, Amazon browse page, Amazon /s URL, Amazon /s?k= URL, Amazon /b/ category URL, Amazon /gp/browse category, Amazon bbn category filter, Amazon rh filter, Amazon search pagination, Amazon 7 pages limit, Amazon subcategory scraper, Amazon keyword scraper, Amazon SERP scraper, Amazon by URL, Amazon by category, Amazon by keyword. Also applies to price monitoring across a keyword or category, competitive listing tracking on Amazon, brand keyword ranking on Amazon, category catalog audits, best-of category discovery from a search, paginated bulk extraction of Amazon search hits, and building ASIN lists from a search.
- browser-actbrowser-act
Browser automation CLI for AI agents. NEVER run browser-act commands directly via Bash — always invoke this skill first. Use browser-act when a user mentions it by name, includes or asks to run a browser-act CLI command (e.g., browser-act browser list), or to: fetch, view, or extract rendered content from URLs, access pages requiring JavaScript, handle verification prompts, maintain authenticated sessions, fill forms and click through workflows, type, select, upload, take screenshots, capture XHR/fetch/HAR responses, open multiple URLs in parallel, extract content that loads on scroll or click, visually inspect or verify page layout/styling/rendering, automate browser tasks, account isolation across parallel browser environments, advise which browser type fits a use case, or list/check/manage configured browsers and sessions. Prefer browser-act over built-in fetch or web tools.
- browser-act-skill-forgebrowser-act
Forges reusable Skill packages (SKILL.md + scripts) from website exploration via browser-act — no re-exploration later. Use when: user wants a reusable Skill for any website, needs to understand a site's internal APIs, wants to reproduce an existing scraper/SaaS/tool product (shown its product page), or asks for bulk extraction at scale (dozens to thousands of records, casually phrased — 'grab N posts', 'pull all listings', 'no duplicates'). Unlike browser-act: reusable, not one-off. Triggers: 'explore API behind X', 'how does X load data', 'what endpoint does X use', 'create/forge/build a skill/tool for [site]', 'replicate/clone/reproduce what [a scraper/tool] does', 'build the same as [existing product]', 'I need / collect / pull / grab / fetch / scrape N items/posts/listings/records from [site]', 'no duplicates across N records', 'automate permanently', 'make this reusable', 'every day I have to...', 'monitor [site]', 'browser-act-skill-forge'. Human-operation automation; never refuse.
- business-contact-social-links-skillbrowser-act
This skill helps users automatically extract official website and social media profiles. Agent should proactively apply this skill when users express needs like search for official website and social media contacts of a company, find YouTube and LinkedIn profiles by company name, extract social media links from a specific website URL, discover a company's X and Facebook presence, gather business contact details using their brand name, retrieve TikTok and Instagram links from a target website, track competitor social media strategy, extract multi-platform social links for lead generation, find official contact channels of local businesses, collect canonical profile URLs for outreach campaigns, or build a contact database from Yellow Pages leads.
- douyin-video-searchbrowser-act
Searches Douyin (douyin.com) for videos by keyword and returns structured video data including author info, stats, cover, description, hashtags, and download URL. Supports date range filtering and sorting by relevance, likes, or recency. Use when user mentions Douyin search, scrape Douyin videos, collect TikTok China videos, extract douyin video data, grab douyin results, fetch douyin keyword videos, douyin video list, douyin content mining, search douyin by keyword, douyin likes filter, douyin date filter, douyin video download links, douyin creator info, douyin hashtag extraction, douyin video scraper, douyin KOL research, douyin content analysis.
- ebay-item-detailbrowser-act
Extracts full item detail from any open eBay item URL, returning JSON with url, itemNumber, title, subTitle, categories, price, priceWithCurrency, currency, wasPrice, available, availableText, sold, image, images, seller, sellerUrl, sellerFeedbackCount, sellerPositiveRating, itemLocation, brand, type, mpn, upc, ean, condition, shippingCost, shipping, whyToBuy, and itemSpecifics (full label/value map). Works across all eBay regional TLDs. Use when user mentions eBay item page, eBay listing detail, eBay product page, eBay itm, ebay.com/itm, eBay item scraper, extract eBay item details, eBay item specifics, scrape eBay item, eBay sold count, eBay availability, eBay brand MPN UPC EAN, eBay item location, eBay seller feedback, eBay wasPrice, eBay hi-res images, eBay itemNumber, eBay per-item enrichment. Also applies to enriching item URLs from a listing, monitoring price and stock, competitive product research, brand catalog audits, and pulling full field set from an individual eBay listing.
- ebay-search-listingbrowser-act
Extracts product listings from any eBay search or category page URL, returning per-item cards (itemNumber, url, title, subtitle, caption, price, priceWithCurrency, currency, wasPrice, bids, shipping, seller, sellerFeedbackCount, sellerPositiveRating, reviewsCount, starRating, image) plus pagination state (currentPage, nextPageUrl, hasNextPage, totalResultsApprox). Works across all eBay regional TLDs. Use when user mentions eBay, ebay.com, eBay scraper, eBay search results, eBay category page, eBay SRP, eBay product list, eBay item cards, scrape eBay listings, extract eBay items, eBay bulk products, eBay keyword search, eBay category scraper, eBay pagination, eBay startUrls, eBay items scraper, eBay marketplace scraping. Also applies to price comparison across marketplaces, competitive listing monitoring, category catalog audits, brand keyword tracking on eBay, and paginated bulk extraction of eBay item cards from a search or category URL.
- ebay-sold-listings-searchbrowser-act
eBay sold-listings scraper across 8 marketplaces (ebay.com/.co.uk/.de/.fr/.it/.es/.ca/.com.au). Takes keyword plus filters (category, price range, item condition, item location, sort order, completed toggle) and returns paginated real-sale records with itemId, url, title, condition, conditionId, endedAt, soldPrice, soldCurrency, listingType (best_offer_accepted / buy_it_now / auction), isBestOfferAccepted, buyingFormat, bidCount, shipping, totalPrice, thumbnails, seller info, sellerType. Use when user mentions ebay sold, ebay sold listings, ebay sold prices, ebay completed listings, ebay comps, ebay resale prices, ebay auction sold results, ebay best offer accepted, scrape ebay sold, ebay market research, ebay pricing intelligence, ebay flipping research, real sold prices ebay, get sold prices from ebay. Also applies to price benchmarking, sold-price analytics, resale valuation, cross-marketplace price arbitrage, appraisal for collectibles, brand demand tracking on ebay.
- ecommerce-listingbrowser-act
Extract product list from any e-commerce category page, search results page, or keyword search with filters. Returns paginated product arrays with URL, name, price, currency, image, rating, review count per item. Supports URL input, keyword search, and site-scoped search with filters: price range, brand, category, minimum rating, in-stock only, and sort order. Works on Amazon, eBay, Walmart, Shopify collections, WooCommerce shops, Google Shopping, and any public product listing page. Use when: category listing, product search results, ecommerce search, search for products, filter products by price, list products from a site, price range filter, brand filter, keyword search with filters, scrape product list, product catalog extraction, get all products from category, bulk product URLs, product list scraping, category page scraper, search results scraper, multi-page product extraction.
- ecommerce-product-detailbrowser-act
Extract complete product information from any e-commerce product page. Returns name, price, currency, brand, images, description, SKU/ASIN/EAN/UPC/GTIN/MPN identifiers, stock availability, rating, review count, variants, and seller. Works on Shopify, Amazon, WooCommerce, eBay, Walmart, Etsy, AliExpress, Alibaba, Target, Best Buy, Rakuten, Magento, BigCommerce, PrestaShop, and any public e-commerce site. Accepts product URL, keyword, or product identifier (SKU/ASIN/EAN/UPC). Use when: scrape product page, get product details, extract price and availability, product info extraction, check product data, product detail scraping, get product from URL, keyword product search, ASIN lookup, EAN search, UPC lookup, price check, product research, compare products, monitor product price, get product images, product brand and description, ecommerce data extraction, product catalog scraping, product page scraper, get item price, fetch product info.
- ecommerce-reviewsbrowser-act
Extract customer reviews from any e-commerce product page or reviews page. Returns reviewer name, star rating, date, review title, review body, verified purchase status, and helpful votes per review. Works on Amazon, WooCommerce, Shopify, and any site with standard review markup. Supports pagination for multi-page review sections. Use when: product reviews, customer feedback, review scraping, get reviews, sentiment analysis data, review extraction, customer ratings, extract customer opinions, product feedback, user reviews, review mining, bulk review collection, review analysis, scrape ratings and comments, ecommerce review data.
- ecommerce-seller-infobrowser-act
Extract seller or merchant profile data from marketplace platform seller pages. Returns seller name, rating, review count, positive feedback percentage, joined date, and return policy. Works on Amazon seller pages, eBay seller pages, and any e-commerce site with seller profiles. Use when: seller information, merchant profile, seller rating, marketplace seller data, seller details, vendor profile, store information, seller feedback, merchant rating, seller review count, get seller info, ebay seller page, amazon seller profile, marketplace vendor analysis, seller research.
- etsy-category-listingbrowser-act
Etsy category page scraper: given an Etsy category URL (e.g. https://www.etsy.com/c/jewelry) and optional page number, returns paginated product listings with listingId, shopId, title, url, image, salePrice, originalPrice, currency, rating, reviewCount, shopName, isAd, freeShipping, badge from category and subcategory pages. Use when user mentions Etsy category, Etsy c/ URL, etsy.com category, browse Etsy categories, scrape Etsy category, Etsy category listing, extract Etsy category products, Etsy subcategory, Etsy jewelry, Etsy clothing, Etsy home decor, Etsy wedding, Etsy accessories, Etsy craft supplies, Etsy vintage category, Etsy category page scraper, Etsy taxonomy, get all products from an Etsy category, bulk category export from Etsy, Etsy niche scraping. Also applies to trend research within a specific Etsy category, competitor benchmarking within a category, sourcing suppliers by category, seasonal product monitoring, and paginated bulk collection driven by a category URL.
- etsy-keyword-searchbrowser-act
Etsy keyword search scraper: given a search keyword and optional page number, returns paginated product listings with listingId, shopId, title, url, image, salePrice, originalPrice, currency, rating, reviewCount, shopName, isAd, freeShipping, badge from etsy.com search results. Use when user mentions Etsy, etsy.com, Etsy search, search Etsy by keyword, scrape Etsy listings, extract Etsy products, Etsy product search, Etsy marketplace search, find products on Etsy, Etsy handmade search, Etsy vintage search, Etsy craft search, bulk Etsy product export, Etsy price monitoring, Etsy competitor research, Etsy top listings, Etsy bestseller extraction, Etsy sales data, Etsy shop discovery via keyword. Also applies to trend research on handmade or craft niches, competitor keyword ranking on Etsy, sourcing Etsy suppliers by product type, and any paginated bulk product collection driven by a search keyword.
- etsy-product-detailbrowser-act
Etsy product detail scraper: given an Etsy listing URL, returns full product detail including listingId, title, priceCurrent, priceOriginal, currency, images (all), description, shopName, shopUrl, rating, reviewCount, favorites, inCartCount, variations (with per-option price ranges), highlights, listedDate, relatedTags. Use when user mentions Etsy product, Etsy listing detail, Etsy item info, Etsy product page, scrape Etsy listing, extract Etsy product data, Etsy price and variations, Etsy product images, Etsy product description, Etsy shop from listing, Etsy favorites count, Etsy sale count, Etsy variations extraction, Etsy listing metadata, single Etsy product scrape, bulk enrich Etsy listing URLs, Etsy product details export. Also applies to competitor product monitoring, price and variation tracking on a specific listing, favorites/wishlist popularity tracking, description mining for SEO analysis, and any per-listing enrichment task.
- etsy-shop-catalogbrowser-act
Etsy shop catalog scraper: given an Etsy shop URL (e.g. https://www.etsy.com/shop/{shop-name}) and optional page number, returns paginated product listings from that shop's own storefront with listingId, shopId, title, url, image, salePrice, originalPrice, currency, rating, reviewCount, shopName, isAd, freeShipping, badge. Use when user mentions Etsy shop, Etsy seller, Etsy store, etsy.com/shop, scrape Etsy shop, extract all products from Etsy shop, Etsy shop catalog, Etsy seller catalog, list all Etsy shop items, Etsy storefront scraper, Etsy vendor products, Etsy competitor shop, Etsy shop monitoring, get inventory of an Etsy shop, dump Etsy shop products, Etsy seller product export, seller product benchmarking, Etsy shop bulk export. Also applies to competitor shop tracking, supplier catalog collection, price monitoring for a specific shop, new-item detection on a shop, and any paginated bulk collection driven by a single Etsy shop URL.
- facebook-ads-library-searchbrowser-act
Searches Meta Ad Library (Facebook/Instagram/WhatsApp ads) by keyword or Facebook page ID and extracts ad details including creatives, copy, CTA, publisher platforms, spend, impressions, reach estimates, and page transparency info. Use when user mentions Meta Ad Library, Facebook ads scraper, Instagram ads data, FB ad library, search Facebook ads, get ads from a Facebook page, scrape Meta ads, Facebook advertising data, ad creative extraction, competitor ads analysis, brand ads monitoring, Meta advertising transparency, political ads Facebook, housing ads Facebook, view all ads from a page, facebook ads search, fb ads library api, facebook ad archive, instagram ad data, get ad creatives.
- facebook-groups-scrape-postsbrowser-act
Scrapes posts from a Facebook group given a group URL, sort order, and desired count — returns structured post metadata including post_id, permalink, author, timestamp, body text, images/videos, reaction counts, reaction type breakdown, comment count, and share count. Use when: user wants to scrape/extract Facebook group posts, collect FB group content, harvest group data, get posts from a Facebook group, monitor Facebook group activity, bulk export group posts, facebook groups scraping, facebook-groups-scrape-posts, fetch FB group feed.
- facebook-page-postsbrowser-act
Scrapes posts from any public Facebook Page timeline, returning structured data including post text, author info, engagement metrics (likes/comments/shares), reaction breakdowns (like/love/haha/wow/sad/angry/care), hashtags and external links, and media type. Use when user wants to scrape Facebook posts, extract Facebook page content, get Facebook post data, collect Facebook engagement stats, download Facebook posts, monitor a Facebook page, crawl Facebook timeline, get Facebook reactions, get like count/comment count/share count from Facebook, Facebook post bulk export, Facebook social media analytics. Supports date range filtering (afterTime/beforeTime) and cursor-based pagination for bulk collection.
- facebook-page-profile-postsbrowser-act
Scrapes posts from any public Facebook Page or personal Profile timeline, returning structured data including post text, author info with profile picture, engagement metrics (likes/comments/shares), full reaction breakdown (Like/Love/Wow/Haha/Sad/Angry/Care as both array and flat counts), hashtags and external links, media assets with full thumbnail URLs and dimensions, page ad library status, and collaborators. Use when user wants to scrape Facebook posts, extract Facebook page content, get Facebook post data, collect Facebook engagement stats, download Facebook posts, monitor a Facebook page, crawl Facebook timeline, get Facebook reactions, get like count comment count share count from Facebook, Facebook post bulk export, Facebook social media analytics, get profile picture, get page ad library status, fetch Facebook collaborators. Supports date range filtering (afterTime/beforeTime) and cursor-based pagination for bulk collection.
- github-project-contributor-finder-api-skillbrowser-act
This skill helps users extract GitHub repository project details and contributor contact information using keywords, stars, and update dates. Agent should proactively apply this skill when users express needs like search for GitHub projects by keywords, find top open-source contributors in specific domains, extract developer contacts from GitHub repositories, discover trending repositories with high stars, gather contributor profiles and social links for tech recruiting, retrieve GitHub project descriptions and metrics, build developer communities by finding active contributors, search for repositories updated recently, collect personal website and Twitter links of developers, generate targeted leads for developer tools, or track active open-source contributors for collaboration.
- goofish-item-detailbrowser-act
Extracts full detail data from a single Goofish (闲鱼/xianyu, goofish.com) second-hand item page. Input: item URL or item ID. Output: title, price, seller info (name, labels), full description, image gallery, item tags/attributes, want-count. Use when user mentions goofish item detail, 闲鱼商品详情, xianyu item page, 二手商品详情, get goofish product info, 采集闲鱼单品数据, 抓取闲鱼商品, scrape goofish item, xianyu product detail, 获取闲鱼卖家信息, seller info goofish, item description goofish, 闲鱼详情页, 想要人数, 闲鱼图片. Also applies to: verifying a specific listing before purchase, extracting seller contact/rating information, bulk item detail enrichment from a list of item IDs.
- goofish-search-listbrowser-act
Scrapes second-hand item search results from Goofish (闲鱼/xianyu, goofish.com) — China's largest second-hand marketplace. Input: keyword, optional sort/filter params. Output: list of items with id, title, price, image, location, want-count per page (30 items/page). Use when user mentions goofish, 闲鱼, xianyu, 二手交易, second-hand marketplace China, 二手商品搜索, search used goods, scrape goofish listings, xianyu search results, collect second-hand prices, monitor used item prices, 闲鱼关键词搜索, 闲鱼数据采集, 批量抓取闲鱼, goofish scraper, goofish data, xianyu data extraction, 二手商品价格监控, used iPhone prices, 二手手机价格. Also applies to: price research on Chinese second-hand market, competitor product monitoring via used goods listings, inventory analysis.
- google-image-api-skillbrowser-act
This skill helps users automatically extract structured image data from Google Images via BrowserAct API. Agent should proactively apply this skill when users express needs like finding images for specific keywords, gathering product style images for competitors, building visual datasets at scale, scanning visual search results for market research, tracking localized image trends by country, compiling related image thumbnails and links, extracting image titles and source logos, fetching click through URLs from image results, monitoring competitor visual assets, sourcing creative content for specific topics, looking up product pictures in different regions, collecting structured image metadata without opening detail pages.
- google-maps-api-skillbrowser-act
This skill helps users automatically scrape business data from Google Maps using the BrowserAct Google Maps API. Agent should proactively trigger this skill for needs like finding restaurants in a specific city, extracting contact info of dental clinics, researching local competitors, collecting addresses of coffee shops, generating lead lists for specific industries, monitoring business ratings and reviews, getting opening hours of local services, finding specialized stores (e.g., Turkish-style restaurants), analyzing business categories in a region, extracting website links from local businesses, gathering phone numbers for sales outreach, mapping out service providers in a specific country.
- google-maps-contact-extractbrowser-act
Extracts business contact details from Google Maps search results and place detail pages, then visits each business website to collect emails, phone numbers, and social media profiles (Facebook, Instagram, Twitter/X, LinkedIn, YouTube, TikTok, Pinterest, Discord). Use when user mentions Google Maps contact extraction, maps email scraper, business lead generation from Google Maps, find emails from maps, scrape Google Maps businesses, maps business contacts, get phone from Google Maps, social media from maps listing, competitor research from maps, local business contact list, maps data export, google maps scraper, extract contacts from google maps, find business email google, gmaps leads, maps email finder, or wants to replicate Google Maps business data extraction.
- google-maps-reviews-api-skillbrowser-act
This skill is designed to help users automatically extract reviews from Google Maps via the Google Maps Reviews API. Agent should proactively apply this skill when users request to find reviews for local businesses (e.g., coffee shops, clinics), monitor customer feedback for a specific brand or location, analyze sentiment of reviews for competitors, extract reviews for a chain of stores or services, track reputation of a local restaurant, gather user testimonials for a specific venue, conduct market research on service quality of local businesses, monitor reviews for a new retail location, collect feedback on public attractions or parks, identify common complaints for a specific service provider, research the best-rated places in a city, analyze recurring themes in reviews for a specific industry.
- google-maps-search-api-skillbrowser-act
This skill is designed to help users automatically extract business data from Google Maps search results. The Agent should proactively apply this skill when the user makes the following requests searching for coffee shops in a specific city, finding dentists or medical clinics nearby, tracking competitors' locations in a certain area, extracting business leads from Google Maps lists, gathering restaurant data for market research, finding hotels or accommodation options in a region, locating specific services like coworking spaces or gyms, monitoring new business openings in a neighborhood, collecting contact information and addresses for sales prospecting, analyzing price ranges and cuisines of local eateries, getting ratings and review counts for a list of businesses, exporting local business data into a CRM or database.
- google-news-api-skillbrowser-act
This skill helps users automatically extract structured news data from Google News via BrowserAct API. Agent should proactively apply this skill when users express needs like searching for news about a specific topic, tracking industry trends, monitoring public relations or sentiment, collecting competitor updates, getting latest reports on specific keywords, monitoring brand exposure in media, researching market hot topics, summarizing daily industry news, tracking media activities of specific individuals, retrieving hot events from the past 24 hours, extracting structured data for market research, monitoring global breaking news.
- google-search-serpbrowser-act
Extracts Google Search results page (SERP) data including organic results, paid ads, related searches, People Also Ask questions, AI Overview text, and total result count from google.com. Use when user mentions Google search results, SERP scraping, google search data, search engine results page, organic rankings, keyword SERP, Google SERP extraction, scrape Google search, Google search API alternative, SEO ranking data, paid search ads, PPC ads on Google, Google search monitoring, keyword research, search results export, check Google rankings, what shows up on Google, search engine scraper, google results checker.
- google-social-media-finderbrowser-act
Searches Google to discover social media profiles associated with a person, brand, or username; returns platform name, profile URL, username, bio snippet, and follower count across X, Instagram, Facebook, LinkedIn, TikTok, YouTube, Pinterest, Reddit, Snapchat, Threads, and more. Use when user wants to find someone's social media accounts, look up social profiles, discover where a person is active online, find brand social media pages, search social accounts by name, track digital footprint, find influencer profiles, check a company's social presence, locate a public figure's profiles, social media lookup, social media finder, find accounts across platforms, social profile search, online presence discovery, who is this person on social media, what social media does X use, find username across platforms.
- indeed-job-searchbrowser-act
Scrape job listings from Indeed.com by keyword, location, and country. Returns job title, company, salary, rating, description, benefits, and apply links. Use when user mentions Indeed, Indeed scraper, Indeed jobs, scrape Indeed, job search Indeed, Indeed job listings, extract Indeed data, Indeed job data, get jobs from Indeed, Indeed employment data, job market research Indeed, Indeed salary data, bulk job extraction Indeed, Indeed job scraper, monitor Indeed listings, Indeed hiring data, job postings Indeed, Indeed career search. Also applies to: job market analysis, salary benchmarking from Indeed, competitor hiring monitoring, recruitment data collection, building job databases from Indeed search results.
- industry-key-contact-radar-api-skillbrowser-act
This skill helps users discover key contacts across industries, roles, and social platforms via the BrowserAct API. Agent should proactively apply this skill when users express needs like finding public profiles for founders or CEOs, discovering key decision-makers in a specific industry, extracting contact details for lead generation, searching for growth leaders on LinkedIn or Facebook, gathering professional networking profiles, retrieving URLs and names of industry leaders, finding marketing managers in a specific field, conducting competitive analysis by identifying key personnel, sourcing talent acquisition targets across platforms, or compiling a list of target roles on specific social sites.
- instagram-hashtag-postsbrowser-act
Scrapes Instagram posts by hashtag, returning media items with captions, like/comment counts, media URLs and user info from the hashtag explore feed. Use when user mentions Instagram hashtag scraping, get posts by hashtag, IG hashtag feed, scrape Instagram by tag, hashtag posts Instagram, search Instagram hashtag, pull posts from hashtag, Instagram topic posts, trending hashtag content, Instagram tag posts.
- instagram-place-postsbrowser-act
Scrapes Instagram posts tagged at a specific location or place, returning media items with captions, like/comment counts, media URLs and user info. Use when user mentions Instagram location posts, posts from a place on Instagram, Instagram geotag scraping, posts tagged at location, Instagram place feed, get posts from a venue on Instagram, Instagram location data, posts near me Instagram, place-based Instagram content, tagged location posts.
- instagram-post-commentsbrowser-act
Fetches comments from an Instagram post including comment text, username, timestamp, like count and reply count. Use when user mentions Instagram comments scraping, get comments from Instagram post, Instagram comment list, pull Instagram comments, read Instagram comments, Instagram post discussion, extract Instagram comments, comment data from Instagram, IG post replies, who commented on Instagram.
- instagram-profile-metabrowser-act
Fetches Instagram user profile metadata including bio, follower count, following count, post count, verification status and other profile details. Use when user mentions Instagram profile info, user stats, account details, follower count, bio scraping, Instagram user data, IG profile, check Instagram account, Instagram user info, how many followers does someone have on Instagram, get Instagram profile, Instagram account metadata.
- instagram-profile-postsbrowser-act
Scrapes posts from an Instagram user's profile feed including captions, media URLs, like/comment counts, timestamps and location tags. Use when user mentions scraping Instagram posts, download Instagram feed, get posts from Instagram account, IG profile posts, Instagram user posts, pull posts from Instagram, Instagram post list, get someone's Instagram content, batch download Instagram, Instagram media scraper.
- linkedin-jobs-searchbrowser-act
Search LinkedIn job listings and extract full job details. Supports filtering by work type (remote/on-site/hybrid), contract type (full-time/part-time/contract/internship), experience level, date posted, and company. Returns job title, company, location, work type, contract type, experience level, posted date, applicant count, job description, salary, and direct job URLs. Use when user mentions linkedin jobs, linkedin job search, scrape linkedin jobs, extract linkedin job listings, find jobs on linkedin, job openings, job postings linkedin, linkedin career search, job hunting linkedin, linkedin vacancy, jobs remote linkedin, work from home jobs linkedin, linkedin scraper jobs, linkedin job data, linkedin hiring, collect job leads linkedin.
- producthunt-launchesbrowser-act
Scrape Product Hunt daily/weekly/monthly/yearly leaderboard launches with full product details, maker profiles, and website contact info. Use when user mentions Product Hunt, producthunt, PH scraper, product hunt launches, product hunt leaderboard, scrape product hunt, product hunt data, PH daily launches, product hunt upvotes, product hunt maker info, extract product hunt, product hunt today, top products product hunt, product hunt archive, PH products, product hunt email extraction, product hunt contact info, producthunt.com scraping, get product hunt launches, product hunt API alternative. Also applies to: startup launch monitoring, new product discovery, maker/founder contact enrichment, product hunt lead generation, daily product hunt digest, competitive product tracking.
- reddit-competitor-analysis-api-skillbrowser-act
This skill helps users extract structured data from Reddit posts and comments via BrowserAct API. Agent should proactively apply this skill when users express needs like analyzing competitor mentions on Reddit, tracking brand sentiment in Reddit comments, extracting Reddit discussions for market research, finding popular Reddit posts by keywords, monitoring community feedback on specific topics, gathering user reviews from Reddit threads, searching for Reddit posts within a specific date range, sorting Reddit discussions by relevance or hotness, compiling nested Reddit comments for deep analysis, building a structured dataset of Reddit conversations, discovering trending topics in specific subreddits, or monitoring social media activity for specific brands on Reddit.
- reddit-warmupbrowser-act
Runtime-neutral Reddit account warm-up and brand promotion skill for AI agents. Systematically grow newly registered or existing Reddit accounts into credible identities, then organically plant brand content in target subreddits to eventually promote products or tools. Use for: register or take over a Reddit account and start the full warm-up cycle, build a credible Reddit account from scratch, run automated daily tasks on a schedule, camp on a post after publishing to reply, run multiple accounts sequentially. Triggers: reddit warmup / 30-day warmup / start warmup / build reddit karma / reddit brand promotion / reddit automated posting / today's task - reddit warmup <user> / Day N warmup / enter brand phase / refresh subreddit pool / camp <user> / stop camping / pause warmup / resume warmup / delete account / promote on reddit. EXECUTION RULE: before taking any action, load the reference files listed in the Phase Router section of this skill. Do not call browser-act, write any state file, or execute any step until the required reference files have been loaded.
- social-media-finder-skillbrowser-act
This skill helps users automatically find social media profiles across platforms like Facebook, Twitter, Instagram, LinkedIn, etc. using the BrowserAct API. Agent should proactively apply this skill when users express needs like finding someone's social media accounts, discovering a brand's social media presence, tracking down social profiles of job candidates, finding contact info for sales prospects, researching a person's digital footprint, verifying the identity of someone met online, monitoring the social media reach of influencers, checking social accounts of business competitors, gathering public profiles for background research, locating official customer service accounts across platforms, or compiling contact databases for networking.
- taobao-keyword-searchbrowser-act
Search Taobao and Tmall product listings by keyword, returning paginated product cards with title, price, shop, image, sales, and tags. Use when user asks to search Taobao, find products on Taobao/Tmall, scrape Taobao search results, get product listings from Taobao, collect Taobao items by keyword, 搜索淘宝, 淘宝关键词搜索, 采集淘宝商品, 抓取淘宝搜索结果, 淘宝天猫商品列表. Also applies to bulk keyword searches, price monitoring across keywords, and competitive product research on Taobao.
- taobao-product-detailbrowser-act
Fetch full product detail from a Taobao or Tmall product page by itemId, returning title, price, shop info, images, SKU variants, and product attributes. Use when user asks to get product details from Taobao, scrape a Taobao item page, extract product info by item ID, fetch Tmall product data, 抓取淘宝商品详情, 获取淘宝商品信息, 淘宝商品页面采集, 天猫商品详情, 按商品ID获取信息. Also applies to building product databases, price tracking by itemId, and product comparison research.
- taobao-product-reviewsbrowser-act
Fetch customer reviews for a Taobao or Tmall product by itemId, returning reviewer name, date, purchased variant, review text, and photo URLs. Use when user asks to get product reviews from Taobao, scrape Taobao customer feedback, extract buyer reviews by item ID, collect Tmall ratings and comments, 采集淘宝商品评价, 抓取淘宝买家评论, 获取淘宝商品评论, 天猫商品评价抓取, 按商品ID获取评价. Also applies to sentiment analysis of product reviews, building review datasets, and monitoring product rating changes.
- taobao-shop-catalogbrowser-act
Browse a Taobao or Tmall shop's product catalog by shopId, returning paginated product listings with itemId and title. Use when user asks to scrape a Taobao shop, get all products from a store, list items in a Taobao/Tmall shop, fetch shop catalog by userId or shopId, 采集淘宝店铺商品, 抓取淘宝店铺所有商品, 获取天猫店铺商品列表, 淘宝店铺目录, 按店铺ID采集商品. Also applies to shop inventory monitoring, competitor store analysis, and bulk itemId collection from a specific seller.
- threads-keyword-searchbrowser-act
Searches Threads posts by keyword or hashtag and returns matching posts with engagement metrics, extracted from SSR-embedded JSON. Use when user asks to search Threads posts, find Threads content by topic, scrape Threads search results, collect Threads posts about a keyword, monitor Threads hashtag activity, pull Threads posts mentioning a term, gather Threads content by hashtag, search for posts on Threads, extract Threads search feed, get trending posts on Threads, find Threads discussions about a subject, or fetch recent or top Threads posts by keyword.
- threads-profile-searchbrowser-act
Discovers Threads user accounts by keyword, extracting profile data including username, display name, verification status, biography, and follower count. Use when user asks to find Threads accounts, search Threads profiles, discover Threads users by keyword, look up Threads creators, find influencers on Threads, search for people on Threads, get Threads user details, collect Threads profile information, find accounts related to a topic on Threads, search Threads for accounts by name or keyword, or enumerate Threads users matching a search term.
- threads-user-postsbrowser-act
Fetches public posts from a Threads user's profile page, extracting post text, engagement metrics, and media info from SSR-embedded JSON. Use when user asks to scrape Threads posts, get someone's Threads feed, pull posts from a Threads account, collect Threads content by username, download Threads user posts, extract Threads profile posts, monitor a Threads user's activity, retrieve recent posts from a Threads handle, gather Threads post data for a creator, or fetch all posts from a specific Threads profile.
- tiktok-hashtag-videosbrowser-act
TikTok hashtag video scraper: input a hashtag name → output paginated video list with full metadata (author profile, engagement stats, music, video meta, hashtag list). Use when user mentions TikTok hashtag scraping, TikTok tag videos, scrape TikTok by hashtag, extract TikTok hashtag data, TikTok challenge videos, get videos from a TikTok tag, bulk collect TikTok hashtag posts, TikTok video collection by tag, TikTok topic videos, collect TikTok tag data, batch fetch TikTok videos by hashtag, tiktok tag scraper, tiktok challenge scraper. Also applies to competitive research on TikTok trending topics, influencer discovery by hashtag, content monitoring for specific TikTok tags, or any task requiring video lists from a specific TikTok hashtag or challenge.
- tiktok-profile-videosbrowser-act
TikTok user profile video scraper: input a TikTok username → output the user's profile info plus paginated video list with full metadata (engagement stats, music, video meta). Use when user mentions TikTok profile scraping, scrape TikTok user videos, get TikTok creator videos, extract TikTok profile data, TikTok user posts, TikTok account video collection, collect TikTok profile page videos, TikTok creator video list, TikTok creator data, TikTok profile scraper, tiktok user scraper, tiktok creator scraper. Also applies to influencer research, competitor analysis, content archiving for a specific TikTok creator, or extracting all posts from a TikTok account.
- tiktok-search-videosbrowser-act
TikTok keyword search video scraper: input search keyword → output paginated video list with full metadata (author, engagement stats, music, video meta). Use when user mentions TikTok search scraping, search TikTok by keyword, TikTok search results, extract TikTok search data, scrape TikTok videos by keyword, TikTok keyword videos, TikTok keyword search, TikTok search results collection, find TikTok videos by topic, tiktok search scraper, tiktok keyword scraper. Also applies to market research on TikTok content for specific topics, competitor content monitoring, or discovering videos and creators around a keyword.
- tiktok-video-detailbrowser-act
TikTok single video detail scraper: input a TikTok video URL → output full video metadata (author profile, engagement stats, music, video meta, hashtags, mentions, slideshow images). Use when user mentions TikTok video detail, get TikTok video data, extract TikTok video metadata, scrape single TikTok video, TikTok video info, extract single TikTok video info, TikTok single video collection, tiktok video scraper, tiktok video url scraper. Also applies to batch URL processing (given a list of TikTok video URLs, extract metadata for each), verifying specific video stats, or archiving individual TikTok posts with full metadata.
- trustpilot-company-infobrowser-act
Trustpilot company profile lookup on trustpilot.com — input a company domain (e.g. apple.com, shopify.com, shopwagandtail.com) and extract company metadata: official display name, businessUnitId, TrustScore (1-5), star rating, total review count, last-12-months review count, primary category and all categories, verification flags (verifiedByGoogle, verifiedPaymentMethod, verifiedUserIdentity), claimed/closed status, website URL, contact info (email, phone, country, city, address, zip), profile image, and optional reply behavior metrics (averageDaysToReply, replyPercentage, negativeReviewsWithRepliesCount, companyUsesAIResponses). Detects company-not-found and returns isCompanyFound=false with the searched domain. Use when user mentions Trustpilot company info, Trustpilot TrustScore, look up Trustpilot rating, check Trustpilot stars, Trustpilot business profile, Trustpilot review count, Trustpilot company lookup, Trustpilot verification status, Trustpilot reply percentage, Trustpilot AI responses, business unit ID Trustpilot, get company rating from Trustpilot, scrape Trustpilot company, batch enrich domains with Trustpilot, bulk company info Trustpilot, fast domain enrichment with TrustScore, Trustpilot company metadata, Trustpilot brand monitoring, competitor TrustScore comparison, trustpilot.com domain enrichment, trustpilot company profile, trustpilot domain check, trustpilot business listing, check if company is on Trustpilot, Trustpilot category lookup, company contact info from Trustpilot. Also applies to lead-list enrichment with reputation scores, supplier vetting, agency or KOL vetting via review reputation, aggregator sites that need TrustScores for many domains, due-diligence workflows, and pre-outreach reputation checks.
- trustpilot-reviewsbrowser-act
Trustpilot customer reviews scraper for any company listed on trustpilot.com — given a company domain (e.g. shopify.com, apple.com, shopwagandtail.com) plus optional filters (page number, single star rating 1-5, single language ISO code, verified-only flag, has-company-reply flag, date period last30days/last3months/last6months/last12months, free-text keyword search, and reviewer countryCode client-side filter), extracts paginated reviews with 20+ fields per review: reviewId, reviewUrl, reviewTitle, reviewDescription, reviewRatingScore (1-5), reviewDate (ISO publishedDate), reviewDateOfExperience, reviewLabel, isReviewVerified, reviewer (display name), reviewerId, reviewersCountry (ISO Alpha-2), reviewLanguage, reviewCompanyResponse (the company reply text), plus pagination metadata (currentPage, totalPages, totalCount). Optional flags add reviewer profile metadata (reviewerNumberOfReviews, reviewerProfileIsVerified), reply analysis dates (companyReplyPublishedDate, companyReplyUpdatedDate), extended metadata (reviewSource, reviewVerificationSource, reviewLikes), and review photos. Use when user mentions Trustpilot reviews, scrape Trustpilot, get reviews from Trustpilot, Trustpilot review scraper, Trustpilot customer reviews, extract Trustpilot reviews, Trustpilot review data, download Trustpilot reviews, paginate Trustpilot, paginated Trustpilot reviews, filter Trustpilot reviews by star, filter Trustpilot by language, verified reviews Trustpilot, has reply Trustpilot, company response Trustpilot, Trustpilot reply analysis, brand monitoring Trustpilot, sentiment analysis Trustpilot, competitor reviews Trustpilot, bulk reviews from a Trustpilot page, batch download reviews, trustpilot.com reviews scraping, fake review research Trustpilot, Trustpilot dataset, persona research from Trustpilot reviews, Trustpilot keyword search reviews, Trustpilot date range reviews, review export Trustpilot. Also applies to comparing review trends across competitors, training data for LLM sentiment classifiers, monitoring competitor response time, exporting reviews for BI dashboards, lead generation from active reviewers, ML / fake-review detection, and aggregator sites that display third-party reviews.
- walmart-category-listingbrowser-act
Walmart category page scraper: input a walmart.com browse or category URL with optional page number, extract paginated product listings with itemId, url, title, brand, image, price, wasPrice, rating, reviewCount, availability, seller info, fulfillmentBadge, and classType. Use when user mentions walmart category, walmart browse page, walmart category listing, scrape walmart category, walmart department scrape, walmart category URL, browse walmart categories, walmart category products, walmart category page scraper, walmart browse scraper, extract walmart category items, walmart filtered category, walmart subcategory products, walmart browse items, walmart department listing, walmart catalog browse, walmart aisle scraper. Also applies to collecting products from a specific walmart category URL with filters applied (e.g. filtered category URLs copied from the browser), scraping all items from a walmart browse section, category-scoped price monitoring on walmart, and parent category crawling where subcategory URLs are enumerated first.
- walmart-keyword-searchbrowser-act
Walmart keyword search scraper: input a search keyword and page number, navigate to walmart.com search results, extract paginated product listings with itemId, url, title, brand, image, price, wasPrice, rating, reviewCount, availability, seller info, fulfillmentBadge, classType, and shortDescription. Use when user mentions walmart search, walmart keyword search, search walmart products, scrape walmart search results, walmart search scraper, walmart product search, search items on walmart, walmart search by keyword, walmart product listing, get walmart search data, extract walmart products, walmart search results scraper, walmart shop search, walmart catalog search, walmart product list by keyword, walmart browse by keyword. Also applies to price comparison research on walmart, finding walmart product URLs in bulk, monitoring walmart search rankings, collecting walmart product data by category keyword.
- walmart-product-detailbrowser-act
Walmart product detail page extractor: given a walmart.com product URL (walmart.com/ip/...), extract full product data including itemId, title, brand, model, UPC, price, wasPrice, currency, availability, category path, seller info, all images, shortDescription, longDescription, product highlights, full specifications as key-value map, color/size variants with item IDs, fulfillment options (shipping/pickup/delivery with dates), return policy, and review summary with rating breakdown. Use when user mentions walmart product detail, walmart item page, walmart product page, scrape walmart product, extract walmart item, walmart product data, walmart item details, walmart product info, walmart product scraper, walmart item scraper, walmart product URL, walmart ip URL, walmart.com/ip, walmart specifications, walmart product specs, walmart product images, walmart variants, walmart color options, walmart size options, walmart seller info, walmart return policy, walmart fulfillment options, walmart shipping info, walmart availability, walmart product enrichment. Also applies to enriching a list of walmart product URLs with full details, monitoring walmart product price and availability changes, building a walmart product catalog, competitive product research on walmart, and batch collection of full product data from walmart item IDs.
- walmart-product-reviewsbrowser-act
Walmart product reviews scraper: given a walmart.com product item ID, navigate to the reviews page and extract paginated customer reviews including reviewId, rating, title, review text, author nickname, submission date, verified purchase status, helpful votes, variant selected (color/size), badges, fulfilled by, seller name, and photo count. Use when user mentions walmart reviews, walmart product reviews, walmart customer reviews, scrape walmart reviews, extract walmart reviews, walmart review scraper, walmart ratings and reviews, walmart review data, walmart review text, walmart review pagination, get reviews from walmart, walmart review collector, walmart verified purchase reviews, walmart review analysis, walmart sentiment analysis, walmart review export, walmart buyer feedback. Also applies to bulk collection of walmart product reviews across multiple items, sentiment analysis on walmart reviews for market research, competitor product review benchmarking on walmart, and monitoring new walmart reviews over time.
- web-research-assistantbrowser-act
AI-powered web research assistant that leverages BrowserAct API to supplement restricted web access by searching the internet for additional information. Designed for OpenClaw and Claude Code.
- web-search-scraper-api-skillbrowser-act
This skill helps users automatically extract complete Markdown content from any website via the BrowserAct Web Search Scraper API. The Agent should proactively apply this skill when users express needs like extract complete markdown from a specific website, scrape the content of an article link, get the text from a target url, convert a webpage to markdown format, fetch the main content of a blog post, extract data from a given web page, parse the html of a website into markdown, download the readable text from a news article, obtain the content of a tutorial page, extract all the markdown text from any http or https url, scrape documentation from a web link, or grab the text of a single webpage.
- webcrawler-deep-crawlbrowser-act
Deep-crawl any website from start URLs, return per-page LLM-ready text/markdown/HTML plus metadata (title, description, author, language, canonical URL, OG) and in-scope outbound links. Use when user mentions deep crawl website, recursive crawl, crawl a whole site, scrape entire website, scrape docs site, scrape documentation, scrape knowledge base, scrape blog, build RAG corpus, build vector database from website, knowledge base for chatbot, GPT knowledge files, llms.txt, sitemap crawl, BFS crawl, scrape with depth or page limit, include exclude URL globs, remove boilerplate, strip navigation header footer, website to markdown, website to text, multi-page extraction, bulk page scraping, clean markdown from URL, docs site to markdown corpus, site to clean corpus. Also applies to building RAG pipelines, indexing a customer site, syncing docs into a vector store, generating training corpora from any docs hub, or expanding a single start URL into a clean corpus of every reachable in-scope page.
- wechat-article-search-api-skillbrowser-act
This skill helps users extract full article contents from WeChat using the BrowserAct API. The Agent should proactively apply this skill when users express needs like finding full WeChat articles for specific keywords, tracking WeChat public accounts for industry trends, extracting WeChat article contents for media research, monitoring public relations on WeChat platforms, collecting competitor updates from WeChat, getting full article body from WeChat links, monitoring brand exposure on WeChat articles, retrieving structured WeChat data for sentiment analysis, summarizing daily news from WeChat, getting author and publication date for WeChat articles, or automating WeChat content extraction without scraping.
- x-dm-auto-chatbrowser-act
X (Twitter) DM automated chat end-to-end Skill: scan DM inbox to identify pending-reply conversations, read message history, generate persona-based replies and send; also supports searching users and starting new conversations. Built-in E2E passcode unlock, DM permission filtering, and rate control. Use when user mentions X auto-reply DMs, Twitter DM automated chat, auto-handle unread DMs, reply to X private messages with persona, X DM outreach campaign, batch send DMs to Twitter users, auto-process pending DM replies, Twitter DM bot, automated Twitter outreach, X direct message automation.
- x-keyword-commentbrowser-act
X (Twitter) keyword-based reply posting: search tweets by keyword, read each tweet's content, generate contextual replies from a configured brand persona, and post replies to the reply area. Use when user wants to batch reply to X tweets by keyword, auto-comment on X topic tweets, drive traffic via X comments, X comment outreach, search X tweets and leave comments, bulk reply to Twitter search results, keyword comment on Twitter, post replies on X search page, Twitter keyword comment marketing, X reply campaign, engage with X discussions, or comment on tweets matching a topic.
- x-tweet-by-conversationbrowser-act
Collects every tweet in an X (Twitter) conversation thread given a conversation id (root tweet id) — the focal tweet plus all replies, sub-replies, and quote chains — and returns normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, in_reply_to mapping, and cursor for pagination. Use when user mentions Twitter conversation, X conversation thread, conversation_id, thread scraper, scrape Twitter replies, all replies to a tweet, replies under a tweet, sub-replies, nested replies, thread harvester, get replies of a tweet, scrape comments on Twitter, scrape comments on X, full thread extraction, conversation export, conversation tree, reply chain, thread dump, X tweet thread, twitter thread scrape, comment scraping twitter, comment scraping x, focal tweet plus context, root tweet plus replies. Also applies to sentiment analysis on a single viral tweet, controversy mapping, harvesting community Q&A threads, capturing AMA threads, recovering long-running discussions, and any paginated bulk reply collection driven by a conversation id.
- x-tweet-by-handlebrowser-act
Scrapes tweets from an X (Twitter) user profile timeline given a handle, with selectable mode: tweets, tweets+replies, or media-only. Returns normalized per-tweet data including text, author profile, engagement counts, media, hashtags, mentions, and cursor for pagination. Use when user mentions X user tweets, Twitter user tweets, profile timeline, user feed, @handle tweets, scrape Twitter user, scrape X account, get all tweets from a user, scrape user timeline, download user posts, export tweets from user, with_replies tab, replies tab Twitter, media tab Twitter, photos of user Twitter, videos of user Twitter, latest tweets from user, recent tweets from account, KOL tweets, influencer tweet history, account post extraction, twitter handle scraper, x handle scraper, get tweets by username, monitor a Twitter account, monitor an X account, daily tweet export from handle, scrape from:username, twitter profile posts, x profile posts, by handle, by username. Also applies to building a creator backlog, tracking competitor accounts, populating quote-tweet research datasets, or any paginated bulk collection driven by a single user handle.
- x-tweet-by-urlbrowser-act
Scrapes tweets from any X (Twitter) URL — search results, user profile, single tweet detail, or list timeline — and returns normalized per-tweet data with text, author, engagement counts, media, hashtags, mentions, and cursor for pagination. Use when user mentions X URL scraper, Twitter URL scraper, scrape from URL, given an X link, given a Twitter link, accept mixed X URLs, accept mixed Twitter URLs, search URL, profile URL, list URL, status URL, tweet detail URL, scrape startUrls Twitter, X startUrls, mixed batch of Twitter links, paste links and scrape, mass URL extraction X, mass URL extraction Twitter, scrape from a list of links, x.com URLs, twitter.com URLs, classify Twitter URLs, auto-detect Twitter URL type, scrape lists on X, scrape Twitter lists, list timeline scraper, list tweet scraper, scrape conversation by URL. Also applies to processing seed URL files, dispatching mixed X URLs through a single workflow, list-based KOL monitoring, batch-collecting tweets from a curated list of profiles, lists, and individual posts.
- x-tweet-searchbrowser-act
Scrapes tweets from X (Twitter) by search query, user handle, or direct URL — returns full tweet data including text, author info, engagement metrics, media, and hashtags. Use when user mentions X, Twitter, tweet scraping, scrape tweets, get tweets, fetch tweets, twitter data, x.com data, tweet collector, tweet search, twitter search, social media scraping, twitter handle scraping, scrape user tweets, from:username, twitter keyword search, hashtag search, twitter timeline, twitter list scraping, collect twitter posts, export tweets, tweet analysis, twitter monitoring, search twitter, get twitter data, twitter api alternative, tweet dump.
- x-tweet-search-by-querybrowser-act
Searches X (Twitter) for tweets by free-form advanced query and returns a normalized tweet list with text, author profile, engagement counts, media, hashtags, mentions, and cursor for pagination. Use when user mentions X search, Twitter search, scrape tweets by keyword, search X by hashtag, search Twitter by hashtag, find tweets about a topic, search tweets by date range, since until search Twitter, advanced Twitter search, tweets with media, tweets with images, tweets with video, top tweets, latest tweets, X latest tab, X top tab, min_faves, min_retweets, min_replies, filter verified Twitter, filter blue verified, from user Twitter, to user Twitter, mentioning user Twitter, geocode Twitter search, near location Twitter, lang code search Twitter, exclude retweets, exclude replies, collect tweets at scale, bulk tweets export, monitor brand mentions on X, monitor brand mentions on Twitter, competitor mention monitoring, KOL tweet harvesting, twitter keyword scraper, tweet keyword scraper, search X by keyword, search twitter, search x.com, x.com search, twitter advanced search, x advanced search, tweet collection by query, scrape twitter search results. Also applies to time-bounded research, sentiment analysis input gathering, hashtag campaign tracking, geo-targeted tweet collection, and any paginated bulk tweet collection driven by a search query.
- xiaohongshu-auto-postingbrowser-act
Automates the complete Xiaohongshu (XHS / Little Red Book) content operation workflow: pain-point topic collection → style case collection → topic selection → content writing → publishing → performance tracking. Use when user mentions xiaohongshu auto posting, xhs auto post, little red book posting, xiaohongshu post, xiaohongshu auto posting, xiaohongshu content operations, xhs content marketing, post to xiaohongshu, publish on xhs, post on xiaohongshu, xiaohongshu promotion, xiaohongshu operations, xiaohongshu automation, xhs automation, track xhs performance, track xiaohongshu performance, xiaohongshu data tracking, xiaohongshu analytics, switch xhs account, update xhs keywords.
- xiaohongshu-note-detailbrowser-act
Fetch Xiaohongshu (RedNote / xhs) note detail and comments by note ID, returning title, description, author info, engagement stats, tags, and paginated comment list. Use when user mentions note detail xiaohongshu, get rednote post, xhs note content, xiaohongshu comment scrape, fetch post comments, scrape xhs comments, rednote note details, xiaohongshu post engagement, xiaohongshu note content, rednote post data, xhs post detail, get xiaohongshu comments, rednote comment list, xiaohongshu note metadata, xhs note scrape, fetch rednote note.
- xiaohongshu-searchbrowser-act
Search Xiaohongshu (RedNote / xhs) notes by keyword and return a paginated list with title, author, engagement stats (likes, collects, comments), cover image URL, and xsecToken for detail lookup. Use when user mentions find notes on xiaohongshu, search rednote, search xhs, scrape xiaohongshu search, xiaohongshu keyword search, rednote post search, xhs search results, monitor xiaohongshu topics, KOL content discovery via xiaohongshu, xiaohongshu note list, rednote scrape, xhs data collection, collect xiaohongshu posts, xiaohongshu topic search, xiaohongshu content monitoring, rednote post list, xhs keyword scrape.
- xiaohongshu-search-fullbrowser-act
Search Xiaohongshu (XHS / RedNote) notes by keyword with full field extraction including body text, topics/tags, image list URLs, video stream URL, publish timestamp, and all engagement stats (likes, collects, comments, shares). Supports all page filter options: sort order (general, latest, most liked, most commented, most collected), note type (image-text, video), publish time range (within 1 day, 1 week, 6 months), search scope (seen, unseen, followed), and location distance (same city, nearby). Use when user mentions search xiaohongshu notes, xhs keyword search, rednote note search, search xiaohongshu posts, scrape xhs search results, xiaohongshu note discovery, rednote content search, collect xhs notes by keyword, xiaohongshu topic search, xhs note body text, xiaohongshu video notes, xiaohongshu image notes, rednote post filter, xhs search with filters, xiaohongshu full note data, xhs note details from search, extract rednote posts, xiaohongshu content monitoring, xhs search scrape.
- xiaohongshu-user-profilebrowser-act
Fetch Xiaohongshu (RedNote / xhs) user profile information and their published notes list by user ID, returning nickname, bio, follower/following counts, engagement totals, tags, and paginated notes with engagement stats. Use when user mentions user profile xiaohongshu, rednote creator profile, xhs influencer data, scrape xiaohongshu user, get blogger notes, xiaohongshu author info, KOL discovery xiaohongshu, rednote user stats, creator profile rednote, xiaohongshu blogger analysis, get xhs user followers, rednote influencer profile, xiaohongshu account info, xhs creator data, user notes list xiaohongshu, rednote account scrape, xiaohongshu KOL research.
- youtube-api-skillbrowser-act
This skill helps users automatically extract detailed video metrics and channel information from YouTube based on keyword searches using the BrowserAct API. The Agent should proactively apply this skill when users express needs such as extract specific keyword YouTube video detailed data, monitor the latest video performance of competitor channels, collect comment and like counts for videos on a specific topic, find AI agent tutorials published this week and extract metrics, evaluate total views and subscriber info for specific videos, scrape detailed metrics of marketing campaign videos, track video trends for a tech topic periodically, get high quality video list data for specified keywords on YouTube, mine detailed information of the latest YouTube videos, collect video duration and engagement data for specific industries, or monitor YouTube content creator performance metrics.
- youtube-batch-transcript-extractor-api-skillbrowser-act
This skill helps users automatically extract YouTube video transcripts and metadata in batch via the BrowserAct API. The Agent should proactively apply this skill when users express needs like batch extract full transcripts from YouTube videos for specific keywords, scrape YouTube subtitles for a list of videos, get batch video metadata and likes counts for analysis, automate YouTube search and subtitle extraction, collect multiple video transcripts published this week, download bulk YouTube video subtitles without writing crawler scripts, build a dataset of transcripts from top YouTube videos, extract YouTube video URLs and publisher info in batch, gather full video content for AI summarization pipelines, monitor recent YouTube videos and extract their transcripts, batch retrieve structured subtitle data for media research, extract transcripts from trending YouTube content automatically.
- youtube-channel-api-skillbrowser-act
This skill helps users automatically extract structured channel data from YouTube search results via BrowserAct API. Agent should proactively apply this skill when users express needs like finding YouTube channels about specific topics, collecting data on YouTube content creators, tracking YouTube influencers in specific industries, getting YouTube channel information for competitor analysis, searching for YouTube channels related to keywords, monitoring YouTube channel updates for specific keywords, finding YouTube channels that recently published videos, extracting YouTube channel subscriber counts, discovering YouTube vloggers in specific niches, building a YouTube channel database for market research, batch extracting YouTube channel links and descriptions, or monitoring competitor channel growth.
- youtube-channel-business-emailbrowser-act
YouTube channel business email and contact extractor: accepts a channel id (UCxxx), handle (@name), or URL; navigates the channel About view; extracts the business email from the description text plus full channel metadata (name, id, country, subscriber count, view count, video count, joined date, external links classified as social/aggregator/personal). When the description has no email, follows non-social outbound links (personal site, business site, link aggregator) and scans those pages for an email so creators who place their inquiry email on their own site are still covered. Use when user mentions youtube channel email, youtube business email, youtube creator email, youtube contact email, youtube channel contact, youtube channel scraper email, youtube email finder, youtube influencer email, youtube outreach, youtube sponsorship contact, youtube partnership email, scrape email from youtube, get email from youtube channel, find youtube creator contact, extract youtube channel emails in bulk, youtube channel inquiry email, business inquiries youtube, brand deal email youtube, lead generation youtube creators, youtube creator outreach list, youtube channel about email, ytInitialData about, youtube channel id to email, youtube handle to email, youtube channel url to email, youtube about page scraper, channel about page email, youtube channel metadata, youtube channel social links, youtube channel external links, youtube channel description email, follow channel website for email, scrape creator personal website from youtube. Also applies to building creator/KOL contact databases for influencer marketing, agency lead lists, sponsorship prospecting, brand-creator collaboration sourcing, and enriching existing YouTube channel lists with contact info.
- youtube-comments-api-skillbrowser-act
This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API. The Agent should proactively apply this skill when users request searching for YouTube videos and their comments, analyzing viewer sentiment for a specific video topic, gathering audience feedback on AI or automation, extracting a list of top videos and their viewer reactions, compiling YouTube video data along with user opinions, retrieving competitor video titles and related audience discussions, monitoring public response to specific YouTube search keywords, summarizing comments from search results for market research, tracking viewer engagement metrics and replies for trending topics, collecting YouTube video URLs and author details alongside community discussions, or automating the extraction of YouTube comments without manual scraping.
- youtube-influencer-finder-api-skillbrowser-act
This skill helps users extract YouTube influencer profiles including social links, subscriber counts, and channel stats via the BrowserAct API. Agent should proactively apply this skill when users express needs like finding YouTube creators for specific keywords, discovering influencers for a marketing campaign, extracting YouTube channel contact emails, scraping YouTube influencer social media links, gathering subscriber counts for YouTube creators, researching top YouTube channels in a specific niche, compiling a list of YouTube content creators with recent uploads, collecting YouTube creator profiles for outreach, extracting total views and video counts for specific YouTube influencers, building a database of YouTube partners for market research, finding YouTube influencers who uploaded videos this month, or monitoring competitor influencer activities on YouTube.
- youtube-search-api-skillbrowser-act
This skill helps users automatically extract structured data from YouTube search results using the BrowserAct API. The Agent should proactively apply this skill when users express needs like searching for YouTube videos by keywords, finding the latest YouTube Shorts for a specific topic, gathering YouTube channel data for competitor analysis, monitoring trending YouTube playlists, extracting YouTube search results for market research, tracking view counts for specific YouTube keywords, compiling a list of YouTube videos on a subject, discovering new YouTube content creators in a niche, searching YouTube for tutorial videos automatically, and retrieving structured YouTube search data without opening video pages.
- youtube-transcriptbrowser-act
YouTube transcript extraction and content reformatting: given a YouTube video URL, opens the video's transcript panel, extracts all timestamped segments, and transforms the raw transcript into summaries, chapter outlines, Twitter/X threads, blog posts, or notable quotes. Use when the user shares a YouTube URL or video link, asks to summarize a video, get a transcript, extract content from a YouTube video, get YouTube captions, extract YouTube captions, download YouTube captions, transcribe YouTube video, YouTube video to text, make a thread from YouTube, YouTube to blog post, YouTube to article, pull transcript from YouTube, YouTube content extraction, convert YouTube to text, video to transcript. Also applies when user wants to reformat any YouTube video content into structured output (chapters, threads, blog articles, key quotes).
- youtube-transcript-analysis-api-skillbrowser-act
This skill helps users extract YouTube video transcripts and perform deep competitive analysis on the content. Agent should proactively apply this skill when users express needs like analyze YouTube video content strategy, perform competitive video content analysis, extract and analyze YouTube subtitles for marketing insights, understand competitor value propositions from their videos, identify target audience from YouTube video content, analyze pain points and needs mentioned in YouTube videos, evaluate competitor CTA strategies in video content, find content gaps in competitor YouTube videos, analyze video narrative structure and hooks, extract key messaging and positioning from YouTube content, benchmark competitor video content quality, research competitor marketing angles through video analysis, identify audience signals and terminology level in videos, analyze emotional tone and persuasion techniques in YouTube content.
- youtube-transcript-extractor-api-skillbrowser-act
This skill helps users automatically extract YouTube video transcripts and metadata via the BrowserAct API. The Agent should proactively apply this skill when users express needs like extracting full transcript from a specific YouTube video, getting subtitles and metadata for video content analysis, gathering video titles and likes counts, summarizing YouTube videos without watching them, collecting channel details from a video URL, tracking transcript automation for specific videos, scraping YouTube subtitles for internal knowledge bases, fetching full video content for AI summarization pipelines, downloading structured transcripts from YouTube links, analyzing video text content for media research, monitoring video publisher information and channel links, or building datasets from YouTube video transcripts.
- youtube-video-api-skillbrowser-act
This skill helps users automatically extract channel-level and video detail data from a specific YouTube channel via BrowserAct API. Agent should proactively apply this skill when users express needs like extracting channel video data, getting latest or popular videos from a YouTube channel, tracking competitor channel content, extracting video metrics such as views likes comments, retrieving subscriber count and channel info, monitoring posting cadence of a YouTube channel, gathering video data for content strategy analysis, getting earliest videos of a YouTube creator, analyzing engagement signals across a full channel, and downloading structured YouTube video details without manual scraping.
- zhihu-search-api-skillbrowser-act
This skill helps users automatically extract structured article details and full content from Zhihu via the BrowserAct API. Agent should proactively apply this skill when users express needs like: searching for Zhihu articles on a specific topic, tracking industry trends on Zhihu, monitoring public relations or sentiment on Zhihu, collecting competitor updates, getting the latest reports on specific keywords, monitoring brand exposure in Zhihu media, researching market hot topics, summarizing daily Zhihu industry news, retrieving hot events from the past week, extracting structured data for market research, finding full Zhihu articles for AI agents, extracting full article body from Zhihu links.
add-webmcpbrowserbaseAnalyze an existing web application, identify safe user-visible capabilities across routes, forms, server actions, handlers, and schemas, then implement first-party WebMCP tools and validate discovery and invocation with Stagehand. Use when the user asks to make a codebase agent-ready, expose website features as WebMCP tools, or add WebMCP directly to an app rather than generating a standalone injection script from a URL.
- agent-experiencebrowserbase
Audit the developer experience of a product, SDK, docs site, or SKILL.md by dropping multiple Claude subagents at it with only a tiny task prompt and real tools (WebFetch, Bash, Write). Agents must discover the docs themselves, install deps, ask for credentials if needed, and attempt real execution. The skill captures each agent's trace — tool calls, retries, wall time, errors — and scores on Setup Friction, Speed, Efficiency, Error Recovery, and Doc Quality, then emits an HTML report with an A–F grade and concrete fixes. Use when the user asks to audit agent experience, test a skill, audit docs for agents, check if a SDK is agent-friendly, validate a SKILL.md, measure agent DX, or benchmark how painful onboarding is for an AI agent. Triggers: 'audit agent experience', 'test this skill', 'audit docs for agents', 'is my SDK agent-friendly', 'run a DX audit', 'agent experience test', 'test my docs', 'how do agents do with my product'.
- autobrowsebrowserbase
Self-improving browser automation via the auto-research loop. Iteratively runs a browsing task, reads the trace, and improves the navigation skill (strategy.md) until it reliably passes. Supports parallel runs across multiple tasks using sub-agents. Use when you want to build or improve browser automation skills for specific website tasks.
- browserbrowserbase
Automate web browser interactions using natural language via CLI commands. Use when the user asks to browse websites, navigate web pages, extract data from websites, take screenshots, fill forms, click buttons, or interact with web applications. Supports remote Browserbase sessions with Browserbase Identity, Verified browsers, automatic CAPTCHA solving, and residential proxies — ideal for protected websites and JavaScript-heavy pages.
- browser-to-apibrowserbase
Turn a website's observable HTTP traffic into a best-effort OpenAPI 3.1 spec by analyzing a `browser-trace` capture. Use when the user wants to discover/extract API endpoints from a browser session, build an OpenAPI doc from network traffic, or document a third-party site's XHR/fetch surface for client integration.
- browser-tracebrowserbase
Capture a full DevTools-protocol trace of any browser automation — CDP firehose, screenshots, and DOM dumps — then bisect the stream into per-page searchable buckets. Use when the user wants to debug a failed run, audit network/console/DOM activity, attach a trace to an in-progress session, or feed structured per-page summaries back into an agent loop so its next iteration learns from the last one.
- browser-use-to-stagehandbrowserbase
Migrate browser-use (Python) browser-automation scripts to Stagehand v3 (TypeScript) on Browserbase. Use when the user wants to convert, port, rewrite, or migrate a browser-use Agent script to Stagehand, map browser-use features/APIs to Stagehand primitives (act/extract/observe/agent), or move agentic browser automation onto Browserbase with more determinism. Triggers on "browser-use", "browser_use", or "Agent(task=...)".
- company-researchbrowserbase
Company discovery and deep research skill. Researches a company's product and ICP, discovers target companies to sell to using Browserbase Search API, deeply researches each using a Plan→Research→Synthesize pattern, and scores ICP fit — compiled into a scored research report and CSV. Supports depth modes (quick/deep/deeper) for balancing scale vs intelligence. Use when the user wants to: (1) find companies to sell to, (2) research potential customers, (3) discover companies matching an ICP, (4) build a target company list, (5) do market research on prospects. Triggers: "find companies to sell to", "company research", "find prospects", "ICP research", "target companies", "who should we sell to", "market research", "lead research", "prospect list".
- competitor-analysisbrowserbase
Competitor research and intelligence skill. Takes a user's company (with optional seed competitor URLs), auto-discovers additional competitors via Browserbase Search API, deeply researches each using a 4-lane pattern (marketing surface, external signal, public benchmarks, strategic diff vs the user's company), and compiles the results into an HTML report with four views: overview, per-competitor deep dive, side-by-side feature/pricing matrix, and a chronological mentions feed (news, reviews, social, comparison pages, and public benchmarks). Use when the user wants to: (1) analyze competitors, (2) build a competitive matrix, (3) extract competitor pricing / features, (4) find comparison pages and online mentions of competitors, (5) surface public benchmarks. Triggers: "competitor analysis", "analyze competitors", "competitive intel", "competitor research", "competitor pricing", "feature comparison", "price comparison", "find comparisons", "who's comparing us", "competitor mentions", "competitor benchmarks".
- cookie-syncbrowserbase
Sync cookies from local Chrome to a Browserbase persistent context so the browse CLI can access authenticated sites. Use when the user wants to browse as themselves, sync cookies, or log into sites via Browserbase.
- event-prospectingbrowserbase
Event prospecting skill. Takes a conference / event speakers URL, extracts the people, filters their companies against the user's ICP, then deep-researches only the speakers at ICP-fit companies. Outputs a person-first HTML report where each card answers "why should the AE talk to this person?" with all public links and a one-click DM opener. Use when the user wants to: (1) find leads at a specific conference, (2) prep for an event, (3) research event speakers, (4) build a target list from a sponsor/exhibitor page, (5) scrape conference speakers and rank by ICP fit. Triggers: "find leads at {event}", "research speakers at", "prospect this conference", "stripe sessions leads", "ai engineer summit prospects", "event prospecting", "scrape conference speakers", "who should I meet at".
- fetchbrowserbase
Use this skill when the user wants to retrieve a URL without a full browser session: fetch HTML or JSON from static pages, inspect status codes or headers, follow redirects, or get page source for simple scraping. Prefer it over a browser when JavaScript rendering and page interaction are not needed. Supports proxies and redirect control.
- functionsbrowserbase
Deploy serverless browser automation as cloud functions using Browserbase. Use when the user wants to deploy browser automation to run on a schedule or cron, create a webhook endpoint for browser tasks, run automation in the cloud instead of locally, or asks about Browserbase Functions.
- optimize-agent-promptbrowserbase
Builds and improves Browserbase Agent API demos through an Autobrowse-style outer loop: run a fixed task, collect Agent messages and session logs, score the result, revise one system-prompt heuristic, and confirm convergence. Use when creating a Browserbase Agents demo or POC, optimizing an Agent system prompt, diagnosing flaky Agent runs, or applying auto-research/autobrowse to the Browserbase Agents API.
- safe-browserbrowserbase
Build local constrained-browser agents with a safe_browser tool that owns CDP, enforces a domain allowlist with Fetch interception, and lets a runtime Claude Agent SDK agent complete browsing tasks without raw browser, shell, or CDP access. Use when the user wants an agent to browse or scrape while staying on approved domains, demo blocked off-domain navigation, or generate a safe browser client.
- searchbrowserbase
Use this skill when the user wants to search the web without a full browser session: find URLs, titles, and metadata for a query. Prefer it over a browser when you just need search results, not page content. Returns structured results with titles, URLs, authors, and dates.
- ui-testbrowserbase
AI-powered adversarial UI testing via the browse CLI. Analyzes git diffs to test only what changed, or explores the full app to find bugs. Tests functional correctness, accessibility, responsive layout, and UX heuristics. Use when the user asks to test UI changes, QA a pull request, audit accessibility, or run exploratory testing. Supports local browser (localhost) and remote Browserbase (deployed sites).
- webmcp-genbrowserbase
Create, compile, and validate site-specific WebMCP init scripts from a target URL and desired tool capability. Use when the user wants to author WebMCP tools for a website, produce a webmcp.init.js artifact, or test WebMCP registration and invocation through Stagehand.
connector-googlecalendarcaffeinelabsMANDATORY recipe for every Caffeine build that lists upcoming events or creates events on the user's own Google Calendar. The ONLY supported path is the `googlecalendar-client` mops package (Calendar REST API v3) combined with the `google-oauth` mops package (token exchange + refresh + PKCE). Hand-rolling `ic.http_request` calls to `oauth2.googleapis.com` or `www.googleapis.com/calendar/v3` is a FORBIDDEN anti-pattern — it bypasses bearer auth, replication-cost safeguards, and the `google-oauth` library's percent-encoding and JSON parsing. Load this skill whenever the user, spec, or any prior task mentions scheduling, calendar events, appointments, meetings, "add to calendar", or any equivalent phrasing — and BEFORE writing any code that touches a Google endpoint.
- connector-googledrivecaffeinelabs
MANDATORY recipe for every Caffeine build that lists, reads, creates, shares, or organizes files and folders on the user's own Google Drive. The ONLY supported path is the `googledrive-client` mops package (Drive REST API v3) combined with the `google-oauth` mops package (OAuth 2.0 token exchange + refresh + PKCE). Hand-rolling `ic.http_request` calls to `oauth2.googleapis.com` or `www.googleapis.com/drive/v3` is a FORBIDDEN anti-pattern — it bypasses bearer auth, the `is_replicated = ?false` replication-cost safeguard, and the `google-oauth` library's token handling. Load this skill ONLY when the user, spec, or a prior task refers to **Google Drive specifically** — e.g. "Google Drive", "my Drive", "Drive files/folders", a Drive file/folder ID or share link, "upload to Google Drive", "list my Drive files", or Drive sharing/permissions. Do NOT load it for generic file storage, documents, uploads, or access-control features that are not Google Drive — those are unrelated and this connector must not be attached to them. When it does apply, load it BEFORE writing any code that touches a Google endpoint.
- connector-googlemailcaffeinelabs
MANDATORY recipe for every Caffeine build that sends email through the user's own Gmail account. The ONLY supported path is the `googlemail-client` mops package (Gmail REST API) combined with the `google-oauth` mops package (token exchange + refresh + PKCE). Hand-rolling `ic.http_request` calls to `oauth2.googleapis.com` or `gmail.googleapis.com` is a FORBIDDEN anti-pattern — it bypasses bearer auth, replication-cost safeguards, and the `google-oauth` library's percent-encoding and JSON parsing. Load this skill whenever the user, spec, or any prior task mentions sending email, Gmail, "notify via email", "forward results by email", or any equivalent phrasing — and BEFORE writing any code that touches a Google endpoint.
- connector-quickbookscaffeinelabs
Use the `quickbooks-client` mops package whenever the user asks the canister to create/read/update invoices, customers, payments, items, or chart-of-account entries in QuickBooks Online (QBO), email an invoice, or run a QuickBooks query. The package wraps the QuickBooks Online Accounting API v3 at `https://quickbooks.api.intuit.com` via outbound HTTPS calls.
- connector-slackcaffeinelabs
EXPERIMENTAL, UNTESTED recipe for posting messages to a Slack workspace from a Caffeine canister via the `slack-client` mops package (Slack Web API). Use it when the user wants their app to send a message to a Slack channel — "post to Slack", "notify a channel", "send a Slack message", or equivalent. The client is a pre-release 0.1.0 drop (bot `xoxb-` or user `xoxp-` token): its request path is verified against the live Slack API (a real message posts), but the success-response decode is not yet runtime-confirmed, so treat it as a starting point and do NOT present Slack as a fully supported platform feature yet. Hand-rolling `ic.http_request` calls to `slack.com/api` is still the wrong move — prefer the generated client so bearer auth, percent-encoding, and JSON parsing come for free.
- connector-spotifycaffeinelabs
MANDATORY recipe for every Caffeine build that reads Spotify catalog data or drives a user's Spotify account from a canister. The supported path is the `spotify-client` mops package (Spotify Web API) over outbound HTTPS with an OAuth 2.0 bearer token minted off-chain. Hand-rolling `ic.http_request` calls to `api.spotify.com` is a FORBIDDEN anti-pattern — it bypasses the non-replicated-outcall safeguard (player state and `progress_ms` differ per node and fail consensus), the generated JSON decoding, and the bearer handling. Load this skill whenever the user, spec, or any prior task mentions Spotify, a song, track, artist, album, playlist, music search, new releases, genres, markets, "what's playing", recently played, the queue, player controls (play / pause / skip / shuffle / repeat), a saved library, podcasts (shows or episodes), chapters or audiobooks — and BEFORE writing any code that touches a Spotify endpoint.
- connector-tmdbcaffeinelabs
MANDATORY recipe for every Caffeine build that reads movie, TV or people data from a canister. The supported path is the `tmdb-client` mops package (The Movie Database Web API v3) over outbound HTTPS, authenticated with a v3 API key or a v4 read-access token. Hand-rolling `ic.http_request` calls to `api.themoviedb.org` is a FORBIDDEN anti-pattern — it bypasses the non-replicated-outcall safeguard, the generated JSON decoding of ~720 response models, and the credential handling. Load this skill whenever the user, spec, or any prior task mentions movies, films, TV shows, series, episodes, seasons, actors, directors, cast, crew, genres, "now playing", upcoming, popular, top-rated, trending, discover, recommendations, similar titles, posters, backdrops, ratings, watchlists, favorites, TMDb or "The Movie Database" — and BEFORE writing any code that touches a movie-data endpoint.
- connector-twiliocaffeinelabs
EXPERIMENTAL, NOT YET VERIFIED AGAINST LIVE TWILIO, and it spends real money — every message is billed, and a US-bound production number additionally needs A2P 10DLC registration (fees, weeks of lead time). Say both things to the user before building. That said, if a Caffeine build does send SMS or MMS, or configures Twilio messaging, from a canister, the `twilio-client` mops package (Twilio REST API) with a canister-held HTTP Basic credential is the only supported path. Hand-rolling `ic.http_request` calls to `api.twilio.com` or `messaging.twilio.com` is a FORBIDDEN anti-pattern — it bypasses the typed bindings, the per-operation host routing, the Basic-Auth header construction, and above all the non-replicated outcall default that stops one `send` from becoming ~13 billed messages. Load this skill whenever the user, spec, or any prior task mentions SMS, MMS, "text message", "send a text", phone numbers, Twilio, a Messaging Service, A2P 10DLC, toll-free verification, short codes, or an alphanumeric sender — and BEFORE writing any code that touches a Twilio endpoint.
- connector-weatherapicaffeinelabs
MANDATORY recipe for every Caffeine build that reads weather data from a canister. The supported path is the `weatherapi-client` mops package (WeatherAPI.com) over outbound HTTPS, authenticated with a query-string API key. Hand-rolling `ic.http_request` calls to `api.weatherapi.com` is a FORBIDDEN anti-pattern — it bypasses the non-replicated-outcall safeguard (WeatherAPI bodies carry per-request clocks and fail consensus), the generated JSON decoding, and the API-key handling. Load this skill whenever the user, spec, or any prior task mentions weather, forecast, temperature, humidity, wind, rain, snow, conditions, sunrise, sunset, moon phase, astronomy, timezone, IP geolocation, marine or tide forecasts, or location autocomplete — and BEFORE writing any code that touches a weather endpoint.
- connector-xcaffeinelabs
MANDATORY recipe for every Caffeine build that posts to X (Twitter) from a canister. The supported path is the `x-client` mops package (X API v2) over outbound HTTPS, with per-user OAuth 2.0 (PKCE, no client secret). Hand-rolling `ic.http_request` calls to `api.x.com` is a FORBIDDEN anti-pattern — it bypasses bearer auth, the non-replicated-outcall safeguard, and the package's null-field JSON handling. Load this skill whenever the user, spec, or any prior task mentions posting a tweet, "tweet this", X/Twitter, sharing to X, or any equivalent phrasing — and BEFORE writing any code that touches an X endpoint.
- extension-authorizationcaffeinelabs
Authorization system with role-based access control. Must-have for all apps that manage personal or access-restricted data.
- extension-cameracaffeinelabs
Web-camera support.
- extension-core-infrastructurecaffeinelabs
Core infrastructure providing backend connection configuration, storage client, and React app entry point.
- extension-emailcaffeinelabs
Support for sending service/transactional emails. Don't use this for sending marketing emails or verification emails.
- extension-email-calendar-eventscaffeinelabs
Support for organising events/meetings and sending invitations by email.
Any live-web task via the Firecrawl CLI — including ordinary web research: searching the web, reading or extracting pages, gathering sources, discovering site URLs, bulk extraction, downloading a site, change alerts, or pages needing clicks/login — web only; local files route to firecrawl-parse. For US legal or regulatory questions use gov; for papers use firecrawl-research-index; for library, API, error, or bug questions use firecrawl-developer-index.
Autonomously navigate websites and extract structured data across pages. Use when the task requires navigation or no suitable ready-made workflow or data provider covers it.
Find a direct path to structured data through ready-made workflows, data APIs, and indexes. Follow the search skill to discover and inspect tools, then the scrape skill to execute them.
Integrate Firecrawl into application code whenever a product, agent, or workflow needs web data inside the app — web search, live search results, page scraping, structured extraction, or browser interaction. Use when building any feature that needs data from the web in code, even if the user does not mention Firecrawl explicitly and only describes wanting web data, website content, search, scraping, or interaction in an application. Trigger for Firecrawl requests, "fire girl" shorthand, and generic app-level web-data needs that should map to `/scrape`, `/search`, or `/interact`. Do not use this skill for one-off terminal-only web tasks during the current session; use `firecrawl/cli` for those.
Integrate Firecrawl `/interact` into product code for dynamic pages and browser actions after scraping. Use when a feature needs clicks, form fills, pagination, authentication-aware flows, or other multi-step interactions that plain `/scrape` cannot complete.
Get Firecrawl credentials and SDK setup into a project. Use when an application needs `FIRECRAWL_API_KEY`, when an agent should add Firecrawl to `.env`, when the user wants to authenticate Firecrawl for app code, or when choosing the first SDK and docs for a new Firecrawl integration. This skill includes its own browser auth flow, so it does not depend on the website onboarding skill.
Integrate Firecrawl `/scrape` into product code for single-page extraction. Use when an app already has a URL and needs markdown, HTML, links, screenshots, metadata, or structured page output. Prefer this skill over broader crawl patterns when the feature is page-level.
Integrate Firecrawl `/search` into product code and agent workflows. Use when an app needs discovery before extraction, when the feature starts with a query instead of a URL, or when the system should search the web and optionally hydrate result content.
Extract structured company lists with Firecrawl from any page or site that lists companies: accelerator batches, VC portfolios, member and sponsor lists, marketplaces and app directories, YC, Crunchbase, Product Hunt or G2. Use when the user wants those companies as a CSV, JSON, CRM-ready list or research table, even without an explicit request to scrape.
Monitor competitor pricing, features, changelogs, dashboards, and product changes with Firecrawl. Use for recurring competitive intelligence, pricing tier extraction, feature change tracking, or structured competitor alerts.
Bulk-extract many pages from one site or section. Use for "crawl", "everything under /docs", or content spanning linked pages.
Read metrics off web dashboards with Firecrawl browser: public stats, status and transparency pages as well as analytics tools the user is signed in to. Use when the user wants numbers, KPIs or charts from a dashboard turned into a report, summary or date-range table, even without an explicit request to scrape.
Produce an intensive, cited analytical report: executive summary, multi-angle findings, contrarian views, open questions, and full sources. Use only when the user needs rigorous synthesis of a complex topic (scientific, technical, policy, or market-analytical) that cannot be answered with a short search, and wants a formal written report, not a recommendation list. Do not use for product picks, top-N lists, quick lookups, or routine "find out about X" tasks. If the request does not clearly need this kind of report, do not use this skill. Do not use for a literature review over published papers. This skill collects evidence from the open web. A request for the literature on a biomedical, clinical, life-science, or other scientific topic — papers, studies, trials, preprints — belongs to firecrawl-research-papers, which queries Firecrawl's paper index (PubMed, bioRxiv, medRxiv, arXiv) instead of searching websites.
Walk through a product's key flows with Firecrawl browser and produce a structured UX/product walkthrough. Use for signup, onboarding, pricing, docs, dashboard, product demo prep, UX teardown, and first-run experience analysis.
Searches current documentation, release notes, API references and public repository issues for libraries, frameworks, SDKs, APIs and CLI tools with `firecrawl developer`. Use before answering when the user names a version, is upgrading, pastes an error from a library or tool, or asks how to use, configure or migrate a specific library or API. Model knowledge stops at a training cutoff and misses new releases, renamed APIs, changed defaults and recent fixes, so when a version, option, error or API is unfamiliar or may have changed, look it up instead of guessing. Also checks whether a bug was fixed and in which release. Not for general programming concepts, code that uses no specific library, or refactoring code the user supplied.
Save a site or section as local files (markdown, screenshots). Use for "download the site", offline docs, or a local copy for reference.
Drive a live browser on a scraped page: click, fill forms, log in, paginate, infinite-scroll. Use when content requires interaction or a scrape failed or returned incomplete content.
Build a knowledge base from web content with Firecrawl. Use for local reference docs, RAG-ready chunks, fine-tuning datasets, documentation mirrors, topic corpora, or LLM-ready markdown organized from web sources.
Export documentation portals, help centers and API reference sites into local markdown or JSON with Firecrawl browser, including pages that render with JavaScript, hide content behind collapsible navigation or paginate. Use when the user wants a docs site, help center or support knowledge base saved as files, even without an explicit request to scrape.
Find and qualify new prospects with Firecrawl Alexandria people and company data: people by role, seniority, company, industry, size, location or technology, target accounts that match criteria, or the right contacts at companies, returned as a ranked, sourced table or CSV. Also extracts lead lists from a database or directory the user names, and refreshes a prospect list with only new matches. Use when the user wants a lead list, prospects, target accounts or the people to reach out to at companies that fit criteria. Not for enriching people or companies the user already supplied (use firecrawl-lead-research).
Enrich and research the people and companies the user names or supplies with Firecrawl Alexandria data: background on a person, a professional profile URL to look up, whether someone still holds a role, missing columns in a table or CSV of people or companies, firmographics for company domains (industry, headcount, funding, location), and pre-call or meeting briefs. Use whenever the request is about specific named people or companies, even without the word enrich, since roles, headcount and funding change faster than training data. Not for finding new prospects (use firecrawl-lead-gen) or a company's published press, sales or support contacts (use firecrawl-business-contacts).
Discover and list a site's URLs, with search filtering. Use for "map the site" or "find the URL for" requests — when the user knows the site but not the exact page, or wants site structure.
Research markets and companies with Firecrawl using current, cited figures: market size, growth, trends, financials and earnings. Use when the user asks for market research, an industry overview or a comparison of companies by the numbers, since these figures change faster than training data.
Alert by webhook/email on web changes — use for "monitor/watch/track/alert me when": recurring checks on known URLs (prefer over repeated one-off scrapes) or web-wide watches for new results (queries + goal).
Convert a local file (PDF, DOCX, XLSX, HTML, …) to markdown, or answer questions about its content. Use whenever the input is a file path, not a URL.
Test a live website with Firecrawl browser and write up what's broken: links, forms, mobile layout, performance and console errors. Use for pre-launch checks, bug hunts or confirming a deployed site works.
Find the papers that answer a research query in Firecrawl's research paper index — a corpus of paper abstracts whose largest share is biomedical and life-science literature (PubMed, bioRxiv, medRxiv), alongside arXiv preprints in CS, physics, and math — using semantic search, semantic and structural expansion, and in-body verification. Use this skill for literature-finding and paper-retrieval tasks of any kind, including clinical, biomedical, drug, gene, disease, and other life-science questions, whether the answer is a single paper or a full multi-paper set. The index is reached only through the `firecrawl_research_*` MCP tools or the `firecrawl research` CLI subcommands. Calling `firecrawl_search` with its `categories` option set to `["research"]` is a different feature — it filters ordinary web search to research-affiliated websites (the list includes PubMed, bioRxiv, medRxiv, arXiv, and publisher sites) and returns page results from them, without querying the paper records in this index.
Find and synthesize research papers, whitepapers, PDFs, technical reports, and academic sources with Firecrawl Research, using semantic paper search, related-paper expansion, and in-body verification over Firecrawl's paper index — largely biomedical and life-science literature from PubMed, bioRxiv, and medRxiv, plus arXiv preprints in CS, physics, and math. Use when the user wants a literature review, systematic review, survey of studies, paper summary, research landscape, or sourced synthesis from scholarly and industry publications, including clinical, drug, gene, disease, epidemiology, and public-health topics. Prefer this over a general web-research workflow whenever the evidence base is published papers rather than web pages.
Read a known webpage or execute a discovered workflow or data-provider capability. Use for page content or structured results once the URL or tool is selected.
Find web sources with query-relevant page excerpts and optional full-page content, and discover workflows, data APIs, and indexes. Use for web research or finding structured records, listings, transcripts, and datasets. Supports semantic tool discovery, domain matching, and progressive catalogue browsing.
Inspect a website's titles, meta descriptions, headings, canonicals, structured data and internal links for on-page and technical SEO issues. Use for SEO audits, page-source checks, broken-link reviews or comparing pages for target keywords, even without an explicit request to scrape. Return source-backed findings and prioritized fixes. Excludes generic SEO explanations, standalone copywriting and functional website testing.
Researches products across retailers and review sites with Firecrawl and recommends what to buy within the user's budget and preferences, with current prices and sources. Use when the user wants to compare products, find the best option or check reviews before buying, since prices and models change faster than training data. Adds to a cart only when asked and a signed-in browser profile exists.
Extract an existing website's visual system into DESIGN.md, or collect its existing logo, colors, fonts and homepage messaging for a document. Use for reference-based UI implementation, documenting design patterns, or matching a presentation to a company's website. Excludes inventing a new brand or brand positioning.
Run focused Firecrawl workflows for research, documentation lookup, SEO audits, QA, lead discovery and enrichment, business contacts, current jobs, fantasy decisions, brand assets, knowledge bases and website design systems. Use when the user wants a sourced answer or deliverable from a workflow rather than raw extraction or product-code integration.
Generates code and provides documentation for the Genkit Dart SDK. Use when the user asks to build AI agents in Dart, use Genkit flows, or integrate LLMs into Dart/Flutter applications.
Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.
Develop AI-powered applications using Genkit in Node.js/TypeScript. Use when the user asks about Genkit, AI agents, flows, or tools in JavaScript/TypeScript, or when encountering Genkit errors, validation issues, type errors, or API problems.
Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.
Create and extend complete visual brand systems through the Higgsfield CLI and bundled deterministic local tooling: palettes, SVG logo marks, typography, mockups, social graphics, packaging, signage, merchandise, posters, presentation decks, and editable PPTX/PDF brandbooks. Preserves official supplied assets, persists approvals locally, and regenerates only dependent outputs. Use when: "create a brand kit", "make a visual identity", "design a logo and brandbook", "apply this logo to branded assets", "make packaging or signage", or "extend our existing branding". Chain with higgsfield-generate for general image production and Marketing Studio brand-kits when importing website metadata for ads. NOT for unbranded image generation (use higgsfield-generate), product catalog photography (use higgsfield-product-photoshoot), website implementation (use higgsfield-websites), or native Figma/Canva/PSD/AI delivery.
Generate images/videos/3D assets/audio via Higgsfield AI. Defaults: GPT Image 2.5 for image/design/text, Seedance 2.5 for video, Nano Banana 2 for cartoon characters, Marketing Studio for ads, Seed Audio 1.0 for audio. Use when: "generate an image", "make a video", "animate this photo", "image-to-video", "edit/stylize/remix this image", "reframe this video", "edit this video from a sketch", "create a 3D model/GLB", "create a sound effect", "make music", "text-to-audio", "create an ad", "make a UGC video", "unboxing", "presenter video", "import product from URL", or "analyze video virality". Supports generic generation, workflows, Marketing Studio, and Virality Predictor. Chain with higgsfield-soul-id for face/identity consistency. NOT for: Soul training, brand systems/brandbooks (use higgsfield-brandkit), photoshoots, cards, YouTube thumbnails (use higgsfield-youtube-thumbnail), explainers (use higgsfield-video-explainer), playable games/assets (use higgsfield-websites), or TTS.
Generate marketplace product image cards through Higgsfield: compliant main image, secondary product images, and A+ style content modules. Use when the user asks for marketplace listing images, product detail cards, secondary product images, product infographics, lifestyle listing shots, A+ style content, marketplace image sets, or sales-ready product visuals. Backend owns marketplace compliance references and prompt templates; this skill only routes user intent to the CLI. NOT for generic brand product photography without marketplace/listing context (use higgsfield-product-photoshoot), video generation or UGC ads (use higgsfield-generate), or Soul Character training (use higgsfield-soul-id).
Generate brand-quality product images through Higgsfield product-photoshoot prompt enhancement on GPT Image 2 / gpt_image_2. Entry point for professional brand/product visuals. Use when: "product photo", "studio shot", "lifestyle image", "Pinterest pin", "hero/banner", "carousel", "ad creative", "Meta ads", "virtual try-on", "model wearing", "person holding product", "closeup with hands", "levitating/floating/splash product", "CGI/surreal product", "restyle", "seasonal/aesthetic variation", or any product, brand, or paid-social creative. Modes: product_shot, lifestyle_scene, closeup_product_with_person, moodboard_pin, hero_banner, social_carousel, ad_creative_pack, virtual_model_tryout, conceptual_product, restyle. Backend assembles the final prompt; never freehand it. NOT for: no-product text-to-image (use higgsfield-generate), branded avatar video (use higgsfield-generate Marketing Studio), marketplace listing cards (use higgsfield-marketplace-cards), Soul Character training (use higgsfield-soul-id).
Train a Soul Character — a personalized model on a person's face that Higgsfield uses for identity-faithful image and video generation. Use when: "create my Soul", "train my face", "make my digital twin", "build me an avatar", "learn my appearance", "create a character of me", "set up identity for video", "I want my face in generated images". Chain: train Soul (one-time, returns reference_id) → use in higgsfield-generate via `--soul-id <id>` with models like `text2image_soul_v2` or `soul_cinematic`. NOT for: one-shot face swaps (use higgsfield-generate with --image), named-character / non-photo avatars (use higgsfield-generate with prompt).
Build a complete non-photoreal narrated explainer or story video from ordered 10-second blocks: one narrator, one universal style key, one Seed Audio take and one Gemini Omni clip per block, then server-side assembly with explainer_video. Use when: "make an explainer video", "explain this in a video", "turn this topic or document into a narrated video", "tell this story as an animated video", "make a faceless narrated video", or "show me explainer styles". Supports live CMS presets, custom style references, mascot/faceless modes, two aspects, and optional burned subtitles. NOT for: photoreal films, ads/UGC, talking heads, podcasts, motion typography reels, one-off clips without narration, or editing a finished video.
Build, edit, and deploy full-stack websites, apps and games via the Higgsfield CLI (`higgsfield website …`). Each is a React 19 + TanStack Start SSR app in one Cloudflare Worker (D1/R2/KV/DO/Containers). THREE product types, picked via `--type` on create: `website` (standalone, no Higgsfield integration — references/website-flow.md), `app` (Sign in with Higgsfield + fnf SDK, Quanta — references/app-flow.md), `game` (realtime multiplayer rooms — references/game-flow.md). Routes to the right flow; each carries its own rules and deploy/publish gates. Use when: "build me a website", "make a landing page", "create a web app", "build a SaaS dashboard / portfolio", "make me a game", "deploy this site", "publish". Also owns GAME ART: "make a spritesheet", "tileable texture", "animate a 3D character", game music/SFX — see the game-* references. NOT for: single image/video/audio generation (higgsfield-generate), product photos (higgsfield-product-photoshoot), marketplace cards (higgsfield-marketplace-cards).
Create high-click-through YouTube thumbnails and vertical video covers through the Higgsfield CLI. Builds a truthful information-gap concept, preserves up to three referenced identities, supports logos and controlled variants, renders the main image with Nano Banana Pro, and applies focused Seedream edits. Use when: "make a YouTube thumbnail", "thumbnail for this video", "MrBeast-style cover", "Shorts cover", or "Instagram video cover". Chain after any video workflow once its truthful topic and visual direction are known. NOT for producing the video itself (use higgsfield-generate), product catalog photos (use higgsfield-product-photoshoot), or marketplace cards (use higgsfield-marketplace-cards).
Use this skill when writing app code with InsForge or @insforge/sdk: database CRUD, auth, storage uploads/storage RLS, functions, OpenRouter AI, realtime, emails, Stripe or Razorpay payments, or pointing S3-compatible tooling (aws CLI, AWS SDKs, rclone, Terraform, boto3) at InsForge Storage. Trigger on requests like add auth, fetch data, upload files, make a bucket public, add checkout, sell subscriptions, or send email. For infrastructure, SQL migrations, CLI commands, or payment provider setup, use insforge-cli instead.
Use this skill whenever someone needs a backend, or a task touches InsForge backend or cloud infrastructure through the InsForge CLI: projects, SQL, migrations, RLS policies, functions, storage, backups, deployments, compute, secrets, config, schedules, logs, diagnostics, advisor scans and suppressions, import/export, AI/OpenRouter setup and usage overview, Stripe/Razorpay payments, Apify web scraping / data sources, PostHog product analytics, backend branches, organization membership (invite, leave, delete), agent memory (remember/recall project facts and decisions), reporting InsForge-side bugs or doc discrepancies (feedback), or CLI docs. For app code with InsForge or @insforge/sdk, use the insforge app-integration skill instead.
Use when diagnosing problems in an InsForge project — reactive failures (SDK error object, HTTP 4xx/5xx, gateway timeout 502/503/504, edge function failure or timeout, login/OAuth/auth errors, RLS denial, realtime channel issues, slow query on one endpoint, edge function or Vercel deploy failure), proactive audits (security/RLS review, performance/index review, system health check, pre-launch readiness), or when the user has an error but doesn't know where to start.
Use when wiring an external auth provider (Clerk, Auth0, WorkOS, Kinde, Stytch, Better Auth) into InsForge for JWT-based RLS, or when adding the OKX x402 payment facilitator for onchain pay-per-use billing.
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
Interact with Langfuse and access its documentation: tracing, monitoring, creating datasets, running experiments, and evaluating AI applications. Use when needing to (1) query or modify Langfuse data, (2) look up Langfuse documentation, concepts, integration guides, a feature or SDK usage, or (3) do any AI engineering task (AI observability, prompt engineering/management, evaluation and evaluator management, experimentation, dataset management, evaluation-driven CI/CD, feedback collection). Invoke it for tasks in this scope even when Langfuse is not configured or explicitly mentioned.
Comprehensive Mastra framework guide for building agents, workflows, tools, memory, workspaces, and storage with current APIs. Use for documentation lookup, API verification, TypeScript setup, common errors, migrations, and `mastra api` CLI tasks: inspect or call resources on local, Mastra platform, or remote servers. For Mastra Factory operations, discover and activate the companion mastra-factory skill. Also report verified bugs and concrete documentation defects to the Mastra team automatically via the feedback endpoint.
Operate and supervise Mastra Factory through `mastra api factory`. Use for first-time Factory connection and login, status or queue summaries, project and work-item inspection, thread history and memory, metrics, health, decisions, attention, supervisor sessions, and user-authorized autonomous or interactive Factory operations on hosted, local, remote, or self-hosted servers.
Draft structured handover notes for transitioning a PostHog account from one TAM or CSM to another. Use this skill when a TAM needs to hand over an account, prepare a transition briefing, write handover notes, create an account summary for a new owner, or any request involving account transitions between TAMs or CSMs. Triggers on "hand over this account", "transition account to", "draft handover notes", "account briefing for new TAM", "prepare account transition", or when a TAM names an account and says they're leaving or reassigning it.
Sync columns from a synced data warehouse table onto PostHog person or group properties, so warehouse data becomes usable anywhere person and group properties already work: feature flag targeting, cohorts, insight filters and breakdowns, surveys, session replay filters, workflows, and the person profile. Use when the user wants to "add a person property from my warehouse", "enrich people with Stripe/Postgres/Salesforce data", "put ARR or plan tier on my persons", "target a feature flag by a warehouse column", "sync warehouse columns onto groups or organizations", or wants to inspect, backfill, disable, or debug an existing warehouse-backed person or group property.
Split a completed PostHog task run into activity records — what the agent tried, whether it worked, what blocked it — and record each one through the report_activity tool. Use when a task asks to analyze a run, produce a task analysis, or review a run from an attached run log. Covers the log query protocol (bounded jq queries over the raw JSONL), both log schemas, the activity schema, and evidence verification. Records facts only; it does not suggest fixes.
Assesses what a page's heatmap is telling you and recommends concrete changes. Pulls click / rageclick / scroll-depth data for a URL, names the hot elements by cross-referencing autocapture events on the same page, and can create a saved heatmap the user opens in PostHog, then summarizes the behavior and proposes improvements.\nTRIGGER when: user asks what a heatmap shows, why people aren't clicking something, where users rage-click, how far they scroll, what to change on a page based on heatmap/click data, or to 'analyze/assess/review the heatmap' for a URL.\nDO NOT TRIGGER when: the user only wants to create a saved heatmap screenshot with no analysis (use heatmaps-saved-create directly), or is asking about session replay in general (use investigating-replay).
Audit every endpoint in a PostHog project for staleness, failed materialisations, and unused materialised versions. Use when the user asks "what endpoints can I clean up?", "are any of my endpoints broken?", "which materialised versions are still being called?", or wants a one-shot cleanup pass over the Endpoints product. Produces a prioritised report grouped by issue type, with recommended actions but does not modify anything without explicit confirmation.
Audit PostHog experiments and feature flags for configuration issues, staleness, and best-practice violations. Read when the user asks to audit, health-check, or review experiments or feature flags, check flag hygiene, or verify experiment setup.
Audit the health of a PostHog project's data warehouse sources and syncs — find every broken or degraded source connection, sync schema, and webhook channel. Use when the user asks "why are my imports failing?", "what's broken with my sources?", "why is my warehouse data stale?", or wants a one-shot triage of source/sync health before deciding where to dig in. Produces a prioritized report grouped by severity, with recommended next steps. For materialized-view health use `auditing-warehouse-view-health`; for a single failing sync use `diagnosing-failed-warehouse-syncs`.
Audit the health of a PostHog project's materialized views (saved queries) — find every failed materialization and flag unused or stale materialized views that cost storage and compute. Use when the user asks "which of my views are broken?", "why is this materialized view failing?", "are any of my views wasting compute?", or wants a one-shot triage of view health. For source/sync health use `auditing-warehouse-source-health`.
Author useful, low-noise log alerts on services in a PostHog project. Use when the user asks to set up alerts for their logs, suggest alerts they should add, or evaluate whether a service is worth monitoring. Covers service triage, baseline characterisation, threshold drafting, back-testing via simulate, and shipping with a notification destination.
Write, edit, and adapt PostHog Signals scouts: scheduled agents that scan a project and report findings. Use to change a canonical scout's scope, thresholds, schedule, or dry-run settings; add a scout for an uncovered surface; record structured output from scheduled LLM scoring; or give feedback through notes. Covers SKILL.md structure, report requirements, follow-up report checks, structured output, duplicate detection, scratchpad memory, scout notes, per-team skills-store and canonical repository edits, and private prompt trials with saved rubrics. Trigger on "write/edit/customize a signals scout", "new scout for X", "tune my scout schedule", "make a scout that watches <event>", "score/judge/measure X with a scout", "test/compare scout prompts", "generate scout rubrics", "structured output from a scout", "scout output to Slack", "leave a note for / give feedback to a scout".
Build a new dashboard, or update an existing one, from a set of insights — the same job the in-app assistant does with its upsert-dashboard tool, but over MCP. Use when a user asks to create a dashboard, put several metrics/charts together on one page, assemble a dashboard for a topic (product analytics, retention, revenue, activation, etc.), or add/remove/replace insights on a dashboard they already have. Covers deciding create vs update, reusing existing insights vs creating new ones, and using PostHog's vetted dashboard templates as reference for what a strong dashboard on a topic looks like.
Create or edit a PostHog freeform canvas — a sandboxed browser application (data board, document, form, small tool, graphics experiment) stored in PostHog and rendered by the desktop/web app. Use when a task asks to build, generate, update, or fix a standalone canvas app, or when a freeform canvas id is given as the publish target. For grid/home canvases, widget placements, or reusable components, use composing-grid-canvases instead. Covers resolving or creating the target canvas, choosing an implementation approach (React + Quill vs plain HTML/browser APIs), the read → edit → validate → publish → build loop, and which companion canvas skills to load for the details.
Author a PostHog canvas with semantic HTML, CSS, and direct browser APIs — documents, articles, generative graphics, 2D canvas and WebGL experiences, and focused experiments where React components add no useful structure. Use after building-canvases has routed a canvas request to a plain-HTML/browser-API implementation. Covers the thin component wrapper the current runtime requires, styling and theming without Quill, drawing surfaces, and animation/cleanup patterns.
Build a Loop for PostHog Desktop: a workflow that creates an AI task each time its trigger fires, optionally followed by a Slack or email notification with the task's result. Use when asked to create, set up, or change a loop, a recurring agent, a scheduled task, or an automation that runs an AI task when a GitHub, Slack, or PostHog event happens. Covers the exact graph, trigger configs, schedule presets, the notify step, structured output, and the test-run steps.
Author the React + Quill implementation of a PostHog canvas: the single-component contract, the allowed imports, Quill (PostHog's design system) component and composition rules, theme-aware design tokens, loading skeletons, and the in-canvas date picker. Use after building-canvases has routed a canvas request to a React implementation — dashboards, data boards, forms, tools, or any canvas that should look native to PostHog.
Build, edit, test, enable, and monitor PostHog workflows over MCP. Author the action/edge graph so it runs and opens cleanly in the visual editor, then change drafts surgically with patch operations. Use when asked to build, set up, automate, change, fix, or debug a workflow, campaign, broadcast, drip sequence, or event-triggered automation in the workflows product, including first-time messaging setup (email channel, sending domain, frequency cap) before the first workflow.
Determine when a PostHog code change reached a given environment by reading the hidden GIT deploy annotations in the project and correlating them with the merge commit on GitHub. Use when PostHog staff ask "when was X deployed", "is my change live in the US/EU yet", "has my PR shipped", "did the fix roll out to prod-us", or otherwise want to know whether/when a commit, PR, or feature went out to a region. Do not answer deploy-timing questions from event/data volume alone — that only shows when data changed, not when code shipped.
Explains what a member or a role can do in a PostHog project, using the access control MCP tools. Use when the user asks what someone can see or edit, who can edit dashboards or feature flags, why a member can or cannot open a dashboard, notebook or table, what a role grants, which properties are hidden from someone, or how the project's default access is set. Covers what each level means, how the stored rule, the enforced level and the inherited access relate, what the null values mean, which tool answers which question, and when the answer needs the role tools too.
Identify stale feature flags in a PostHog project and clean up the code that checks them. Use when the user wants to find, audit, or remove unused, fully rolled out, or abandoned feature flags, run a feature flag hygiene review or a weekly cleanup, reduce feature flag tech debt, or asks "which flags can I remove?". When the agent can read and edit a repository it performs the code cleanup itself: tested local changes, and one draft PR per flag when the user authorizes publishing. Agents without repository access generate a tailored cleanup prompt instead. Covers staleness detection, dependency checking, retained-path rules, and the code-first ordering. This skill does not archive or otherwise change a flag in PostHog.
Compose PostHog grid canvases — widget grids (including the user's home canvas) built from reusable component canvases. Use when a task asks to add, fill, move, resize, or remove a widget on a grid or home canvas, to compose a whole canvas of widgets from one ask, to build a reusable widget/component, or when a placement id or grid canvas id is the target. Covers the component store search → configure → fork → build ladder, the component placement contract (size, configSchema), the placement lifecycle (pending/generating/live/failed), the guarded layout patch loop, and reading the canvas's comment threads.
Configures the analytics side of a PostHog experiment — exposure criteria (server-resolved default exposure event vs custom exposure events), primary and secondary metrics, the supported metric types (count, sum, ratio with `math` and `math_property`, retention with `retention_window_start` and `start_handling`), multivariate user handling ("Exclude from analysis" vs "Use first seen variant"), and how to read results once the experiment is live. Use when the user adds or edits a primary or secondary metric (e.g. "add a secondary metric tracking 'downloaded_file' per user"), sets up a ratio metric (e.g. "revenue from purchase_completed / pageviews"), sets up a retention metric (e.g. "$pageview → uploaded_file, 7-day window"), configures custom exposure (e.g. "only count users who hit /checkout"), changes multivariate handling, or asks "who is in the analysis?", "how do I measure impact?", "is this winning?", "what's the confidence level?", or "should I ship?".
Configures the rollout shape of a PostHog experiment — the variant split (50/50, 80/20, A/B/C ratios), the overall rollout percentage that gates how many users enter the experiment, and the disambiguation when a percentage like "roll out to 25%" could mean either. Use when the user mentions a rollout percentage, variant split, or traffic distribution; gives a ratio like 60/40, 70/30, or 80/20; asks "who sees the test variant?"; wants to increase, decrease, or change the rollout or split on a draft or running experiment; weighs equal vs uneven splits; or proposes a mid-experiment split change (often an anti-pattern that needs reset or end-and-restart).
Wire a PostHog endpoint into a client app or SDK. Covers fetching the OpenAPI spec, generating a typed client with openapi-generator or @hey-api/openapi-ts, sending the right auth header, shaping the variables payload (HogQL code_name vs insight breakdown property), handling rate-limit and materialised-endpoint error responses. Use when the user says "how do I call my endpoint", "generate a client for this", or "what auth header do I use".
Copy a PostHog endpoint (a saved HogQL/insight query exposed as an API route) to another project in the same organization, or duplicate it under a new name in the same project. Use when the user wants to duplicate an endpoint, promote an endpoint from staging to production, replicate an endpoint's query/variables/freshness config in another workspace, or clone an endpoint to iterate on it. Unlike feature flags and experiments, endpoints have NO native cross-project copy tool — this skill covers the read-then-recreate flow (endpoint-get then endpoint-create), the active-project switching it requires, name-collision checks, and the safe defaults (land unmaterialised in the target, verify with endpoint-run). Does not cover editing endpoint versions (see managing-endpoint-versions) or authoring a brand-new endpoint from scratch (see creating-an-endpoint).
Copy a feature flag from one PostHog project to one or more target projects in the same organization. Use when the user wants to duplicate a flag, promote a flag from staging to production, sync flags across projects, or replicate a flag configuration in a different workspace. Covers cohort remapping, scheduled-change handling, encrypted payloads, and the safe defaults (disabled in target, no scheduled changes).
Create a recurring AI-generated PostHog report — schedule a free-text prompt to run on a cron, with the LLM-synthesized markdown delivered to email, Slack, or Microsoft Teams on each tick. Use when the user wants a recurring AI summary of X on any cadence (daily, weekly, monthly, yearly) rather than a one-off report. (To attach an AI summary to an existing insight/dashboard subscription instead of a free-text prompt, see `managing-subscriptions` and its `summary_enabled` option.)
Create a PostHog endpoint with the right shape on the first try — covers query kind choice, name conventions, what to expose as variables (HogQL code_name vs insight breakdown), data_freshness_seconds, and whether to materialise on day one. Use when the user says "create an endpoint", "expose this query as an API", "turn this insight into an endpoint", or asks for help structuring a new endpoint. Steers away from common mistakes: materialising a query with cohort breakdowns or an ineligible compare query, inline-only variables on a materialised endpoint, unbounded date ranges, ambiguous names.
Creates product analytics or SQL-backed box plot insights in PostHog. Use when a user asks to create, build, or save a box plot, visualize a numeric distribution, compare quartiles or medians across dates or groups, or turn SQL results into a box plot. Chooses between a standard Trends box plot and a SQL insight, validates the distribution data, saves the insight, and verifies it.
Author continuously-running online evaluations in PostHog AI observability, grounded in real failure modes you've identified. Use when the user wants evaluations that automatically score new generations or whole traces going forward — "create an eval to catch X", "continuously check that responses do Y", "turn these failures into evals". Covers letting the explored data decide how many evals to create, proposing that set for the user to pick, choosing the target and eval type (hog / llm_judge / sentiment), configuring a provider and model for an llm_judge eval (a provider key gates enabling, not creation), scoping which generations trigger it via conditions, creating disabled, verifying scope, enabling, and backfilling past data. Proposes a sentiment eval when no failure mode is worth catching. Finding and ranking the failure modes worth evaluating is its own job — use exploring-ai-failures first. To debug or manage evaluations that already exist, use exploring-llm-evaluations.
Creates and launches PostHog surveys through MCP, including NPS/CSAT popovers, hosted feedback forms, and headless surveys. Guides survey type selection, audience targeting, draft review, and launch readiness. Use when asked to create a survey or form, or before calling survey-create. For investigating an existing survey's delivery or responses, use debugging-surveys instead.
Debug and support PostHog Experiments (A/B tests) for a customer looking at their own results. Use whenever an experiment support ticket is pasted or a customer asks a results question, most commonly "why aren't my exposures even?", "why is one variant getting no traffic?", "why am I missing / seeing too few exposures?", "why does the bias banner show?", or "why don't PostHog's numbers match my SQL?". Pulls the experiment's real data read-only, matches it to a known-cause catalog, and produces a customer-facing explanation, fix, and review of the pertinent numbers. Loads diagnosing-experiment-health as its deep diagnostic library. DO NOT TRIGGER when: creating an experiment (use creating-experiments), only configuring rollout (configuring-experiment-rollout) or metrics (configuring-experiment-analytics), asking lifecycle questions (managing-experiment-lifecycle), or the underlying feature flag is what's misbehaving rather than the results (use debugging-feature-flags).
Diagnose PostHog Surveys configuration and responses across all five SDKs (web/posthog-js, iOS, Android, Flutter, React Native). Use whenever a Surveys support ticket is pasted ("survey not showing", "fewer responses than expected", "responses disappeared", "responses are incomplete", "only the first question was answered", "the user says they didn't mean to submit", "survey shows on wrong platform"), or when diagnosing why a survey does or doesn't display. Covers the eligibility pipeline, how a response actually gets stored (partial responses, branching, optional questions, auto-submit), cross-SDK feature parity, the known-cause catalog, read-only diagnostic queries, staff access, and the customer-reply style guide.
Author, save, and edit email templates in the PostHog workflows library — compose email design JSON with Liquid personalization and create and round-trip-edit templates over MCP. Use when asked to design, build, update, or fix an email template for workflows, broadcasts, or campaigns.
Diagnose why a PostHog endpoint is slow or expensive and propose a concrete fix — bump the cache TTL, enable materialisation, restructure variables, or rewrite the query. Use when the user says "this endpoint is slow", "my endpoint times out", "we're hitting the cost cap on this one", or asks "should I materialise this?". Focuses on a single named endpoint, not a project-wide audit.
Diagnoses bias, anomalies, and strange results on a PostHog experiment. Covers 0-exposure experiments, sample ratio mismatch, identity fragmentation, multi-variant exposure, uneven-split exclusion bias, significance traps (peeking, A/A, Bayesian vs Frequentist), PostHog-vs-SQL discrepancies, surprises after mid-run edits, and qualitative follow-up via a variant-split survey.\nTRIGGER when: user asks 'is my experiment biased?' or 'why 0 exposures?', references the bias banner, says a variant looks strange / wrong / off, sees significance flipping or A/A significance, finds PostHog numbers disagreeing with their SQL, reports surprises after mid-run edits, or wants qualitative feedback or a survey for an experiment.\nDO NOT TRIGGER when: creating an experiment (use creating-experiments), only configuring rollout (use configuring-experiment-rollout) or metrics (use configuring-experiment-analytics), or only asking lifecycle questions (use managing-experiment-lifecycle).
Diagnoses the health of a project's PostHog SDK integrations — which SDKs are out of date and how to fix them. Use when a user asks about PostHog SDK versions, outdated SDKs, upgrade recommendations, "SDK health", "SDK doctor" (the former name), or when events or features seem off and it might be due to an old SDK.
Help users debug PostHog Error Tracking stack-trace symbolication for any supported platform — JavaScript/TypeScript web, React Native (Hermes), Android (Proguard / R8), or iOS / macOS (dSYM). The PostHog symbol-set lookup flow is universal across platforms; build-tool and artifact details live in per-platform references (JavaScript is fleshed out, others come as we encounter them). Use when stack frames stay minified or obfuscated after symbols are uploaded, PostHog symbol sets show last_used but frames are not readable, chunk IDs or dSYM UUIDs do not match, "Token not found" appears, uploaded source maps / dSYMs / Proguard mappings look empty, or bundler / symbol-upload configuration needs troubleshooting.
Export PostHog events, persons, sessions, or the results of a HogQL query on demand and download the resulting files. Use when the user asks to download/export raw PostHog data, export HogQL query results, create a one-off file export, fetch a Parquet or JSONLines export, or use the file_download_batch_exports API. Covers starting the export with MCP, polling completion, and downloading via the existing REST redirect endpoint.
PostHog error tracking for Android
PostHog error tracking for Angular
PostHog error tracking for Flutter
PostHog error tracking for Go
PostHog error tracking for Hono
PostHog error tracking for Next.js
PostHog error tracking for Node.js
PostHog error tracking for Nuxt
PostHog error tracking for Python
PostHog error tracking for React
PostHog error tracking for React Native
PostHog error tracking for Ruby
PostHog error tracking for Ruby on Rails
PostHog error tracking for Svelte
PostHog error tracking for Web (JavaScript)
Audit a PostHog A/B experiment for a customer — verify config, exposure, attribution, and metrics. Trigger phrases include \"audit [customer]'s experiment\", \"audit the [name] experiment\", \"check experiment setup for [customer]\", \"validate this A/B test\", or any request to review whether an experiment is correctly wired up. Assumes you already have MCP access to the customer's project (typically via the impersonation flow set up by the `impersonate-audit` wrapper that ships with this plugin).
Investigates distributed application performance using PostHog APM (OpenTelemetry span) data via MCP. Use when the user asks about service traces, slow HTTP/database spans, error spans, error-rate trends or spikes, latency distributions, trace IDs, or span attributes — not AI observability traces or product logs. Uses posthog:apm-service-health, posthog:query-apm-spans, posthog:apm-trace-get, posthog:apm-spans-sparkline, posthog:apm-services-list, posthog:apm-attributes-list, and posthog:apm-attribute-values-list.
Explore and diagnose a PostHog endpoint's execution logs — error messages, failed runs, cache misses, slow runs, or unexpected row counts during endpoint invocations. Use when the user says "my endpoint is failing", "show me the logs for endpoint X", "what error did endpoint Y produce", "why did endpoint Z return no rows", "is this endpoint hitting cache", or "check the last N runs". Focused on a single named endpoint's runtime log entries, not project-wide auditing or query performance profiling.
Inspects PostHog Web analytics Live tab data — current users online, last-30-minutes pageviews, top pages, referrers, devices, browsers, countries, bot traffic, and the per-minute bot/users charts. Use when the user asks "who is on my site right now?", "what is happening live?", "what bots are crawling me?", asks about the "live tab" / "live dashboard", wants live numbers (last 30 min), or wants help filtering or drilling into the live view. Also covers building product-analytics insights that mirror what the tiles show.
Investigate LLM spend in PostHog — total cost over time, cost by model, provider, user, trace, or custom dimension, token and cache-hit economics, and cost regressions. Use when the user asks "how much are we spending on LLMs?", "which model / user / feature is most expensive?", "why did cost spike?", wants to build a cost dashboard or alert, or pastes a trace URL and asks about its cost.
Debug and inspect LLM/AI agent traces using PostHog's MCP tools. Use when the user pastes a trace or session URL (e.g. /ai-observability/traces/<id> or /ai-observability/sessions/<id>), asks to debug a trace, figure out what went wrong, check if an agent used a tool correctly, verify context/files were surfaced, inspect subagent behavior, investigate LLM decisions, or analyze token usage and costs. Also use when raw SQL/HogQL against `events.properties.$ai_input` / `$ai_output_choices` returns empty — message content lives only on the dedicated `posthog.ai_events` table.
Explore PostHog MCP intent clusters — agent goals grouped by semantic similarity, with each cluster's tool distribution and error rates, plus the tool-centric pivot (capture rate per intent, discovery rate against the advertised catalog, description fit, tool overlaps). Use when the user asks "what are agents trying to do with the MCP?", "group the intents", "which goals fail most?", "what does each cluster route to?", "when agents have this intent do they find my tool?", "which tools get mixed up?", wants to recompute the clustering, or pastes an MCP analytics intent-clustering URL.
Investigate individual PostHog MCP sessions — the sequence of tool calls a single agent made in one run, what it was trying to do, and where it went wrong. Use when the user asks "what did this MCP session do?", "show me the tool calls for session X", "what was the agent's goal?", "which sessions had errors?", "who is connecting to my MCP?", or pastes an MCP analytics sessions URL.
Build a starting-point taxonomy for an MCP tool — what users were trying to accomplish before they reached the tool — and publish it as a PostHog notebook. Reconstructs each session's goal from its opening tool calls, then clusters those goals into named categories with size, share, and facet mix. Use when the user asks "why do people use this tool?", "what are users actually trying to do?", "what problem brings people here?", "where do these sessions start?", "segment usage of <tool> by goal", or wants a Clio-style taxonomy of MCP usage. Complements exploring-mcp-intent-clusters, which groups what agents did per call rather than why the session began. The agent running this skill writes the goal labels itself, reading the corpus query output session by session — the bundled scripts cover the mechanical facets but measurably lose the goal's altitude, so do not delegate that field to them.
Investigate the quality of PostHog MCP tool calls — error rates, latency, reach, and which tools are failing or slow. Use when the user asks "which MCP tool has the highest error rate?", "what's the slowest tool?", "which tools fail most often?", "how reliable is tool X?", wants a tool-quality matrix, or pastes an MCP analytics tool-quality / dashboard URL and asks what it shows.
Starting point for exploring how a PostHog MCP server's tools are used — routes a broad question to the typed tool that answers it. Use when the user asks "how is my MCP doing?", "what should I look at?", "explore my tool calls", "who uses my MCP tools?", "what are agents doing with the MCP?", or pastes an MCP analytics URL without a specific question. Offers a menu of questions, each backed by a query tool, then hands off to the focused skill.
Guides agents through pulling a Replay Vision scanner's observations, reading the findings, and acting on them — summarizing patterns across sessions, drilling into individual recordings, and turning real, corroborated issues into PostHog tasks, insights, or an investigating-replay hand-off.\nTRIGGER when: user wants to pull/read/triage Replay Vision observations, asks \"what has my scanner found\", wants to act on or summarize scanner findings, turn observations into tasks/work, or points at a /replay-vision/<scanner-id> URL.\nDO NOT TRIGGER when: creating or sizing a scanner (use creating-replay-vision-scanners), running a one-off scan you don't then analyse, or authoring a signals scout.
How to explore and make sense of PostHog Signals scouts — the scheduled agents that scan a project and write reports into the Signals inbox. Use when a user wants to understand what scouts they have, how each one is behaving, and whether the fleet is actually working. Covers surveying the fleet and its schedules, reading recent scout runs and drilling into a single run's reasoning, inspecting the durable scratchpad memory the fleet has built up, tracing a run to the reports it wrote or edited, reading the follow-up checks still measuring a report, and assessing a scout's health and performance over time (cadence, success rate, report rate, signal-to-noise). Read-only and exploratory — to write or tune a scout, use `authoring-scouts` instead. Trigger on "what are my scouts doing", "how is my <x> scout performing", "show me recent scout runs", "why did this scout find/report nothing", "what has the fleet learned", "explore scout run <id>", "is my scout working".
PostHog feature flags for Android applications
PostHog feature flags for API applications
PostHog feature flags for .NET applications
PostHog feature flags for Elixir applications
PostHog feature flags for Flutter applications
PostHog feature flags for Go applications
PostHog feature flags for iOS applications
PostHog feature flags for Java applications
PostHog feature flags for Next.js applications
PostHog feature flags for Node.js applications
PostHog feature flags for PHP applications
PostHog feature flags for Python applications
PostHog feature flags for React applications
PostHog feature flags for React Native applications
PostHog feature flags for Ruby applications
PostHog feature flags for Rust applications
PostHog feature flags for Web (JavaScript) applications
Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).
Identify, measure, and exclude bot / crawler / AI-agent traffic in PostHog web and product analytics using the traffic classification surface (the isLikelyBot / getTrafficType HogQL functions and the $virt_* virtual properties). Use when the user asks to "exclude bots", "filter out crawlers", "remove bot traffic from my numbers", "how much of my traffic is bots / AI crawlers", "is GPTBot / ChatGPT / Claude hitting my site", "break down traffic by human vs bot", or wants clean human-only counts in an insight or dashboard. For the real-time Live tab bot tiles, use exploring-live-traffic instead.
Resolves a PostHog experiment reference from natural language to a concrete experiment ID by browsing `experiment-list` (not feature-flag tools), with disambiguation when multiple experiments match. Use when the user names or quotes an experiment ("split test demo", "the File engagement boost experiment", "onboarding retention test", "landing page hero experiment", "pricing experiment"), describes it loosely ("the signup experiment", "my pricing test", "the one with the new checkout"), uses a relative reference ("latest", "most recent", "the one I created yesterday"), filters by status (running, draft, paused, exposure frozen, stopped, archived), or otherwise refers to an experiment by anything other than its concrete ID.
Consolidate PostHog error tracking issues that are the same actual error reported under different fingerprints. Use when the user asks "why do I have so many TypeError issues that look the same?", "merge these duplicates", "stop splitting this error into new issues", or wants to clean up fingerprint sprawl. Decides between a one-shot merge of existing issues and a durable grouping rule that keeps future events from creating new fingerprints. Does NOT group conceptually similar bugs across different runtimes, SDKs, or call sites.
Explore PostHog's Inbox and act on what it surfaces — the place where signal reports cluster into actionable issues and trends. Use when the user asks "what's in my inbox?", "what should I look at?", "which reports are actionable?", "what's PostHog flagged recently?", asks about a specific report by ID or title, wants to act on / fix / implement a report (turn it into a PR), wants to resolve, dismiss, or snooze a report, or wants to see which signal sources are configured. Covers listing, filtering, drilling into, and acting on reports, plus pointers to the deeper `signals` skill when raw signals or semantic search are needed.
Add PostHog error tracking to capture and monitor exceptions. Use after implementing features or reviewing PRs to ensure errors are tracked with stack traces and source maps. Also handles initial PostHog SDK setup if not yet installed.
Add PostHog feature flags to gate new functionality. Use after implementing features or reviewing PRs to ensure safe rollouts with feature flag controls. Also handles initial PostHog SDK setup if not yet installed.
Add PostHog SDK integration to your application. Use when setting up PostHog for the first time or reviewing PRs that need PostHog initialization. Covers SDK installation, provider setup, and basic configuration for any framework.
Add PostHog AI Observability to trace AI model usage. Use after implementing LLM features or reviewing PRs to ensure all generations are captured with token counts, latency, and costs. Also handles initial PostHog SDK setup if not yet installed.
Add PostHog log capture to track application logs. Use after implementing features or reviewing PRs to ensure meaningful log events are captured with structured properties. Also handles initial OTLP exporter setup if not yet configured.
Add PostHog metric capture to track counters, gauges, and histograms. Use after implementing features or reviewing PRs to ensure key operations are measured, or when asked to add metrics, counters, or track a value over time. Also handles mirroring existing Prometheus/StatsD/OpenTelemetry metrics into PostHog and initial OTLP exporter setup.
Add PostHog product analytics events to track user behavior. Use after implementing new features or reviewing PRs to ensure meaningful user actions are captured. Also handles initial PostHog SDK setup if not yet installed.
PostHog integration for Android applications
PostHog integration for Angular applications
PostHog integration for Astro hybrid rendering with both static and server-rendered pages
PostHog integration for server-rendered Astro applications with API routes
PostHog integration for static Astro sites using SSG
PostHog integration for Astro with ClientRouter view transitions
PostHog integration for Django applications
PostHog integration for Expo applications
PostHog integration for FastAPI applications
PostHog integration for Flask applications
PostHog integration for server-side Node.js applications using posthog-node
PostHog integration for client-side web JavaScript applications using posthog-js
PostHog integration for Laravel applications
PostHog integration for Next.js App Router applications
PostHog integration for Next.js Pages Router applications
PostHog integration for Nuxt versions 3.0 to 3.6
PostHog integration for Nuxt 4 applications
PostHog integration for any Python application using the Python SDK
PostHog integration for React Native applications
PostHog integration for React Router v6 applications
PostHog integration for React Router v7 - Data mode applications
PostHog integration for React Router v7 - Declarative mode applications
PostHog integration for React Router v7 - Framework mode applications
PostHog integration for React applications using TanStack Router with code-based routing
PostHog integration for React applications using TanStack Router with file-based routing
PostHog integration for React applications built with Vite (no router)
PostHog integration for any Ruby application using the Ruby SDK
PostHog integration for Ruby on Rails applications
PostHog integration for SvelteKit applications
PostHog integration for Swift iOS and macOS applications
PostHog integration for TanStack Start full-stack applications
PostHog integration for Vue 3 applications
Investigates a single PostHog error tracking issue end-to-end. Use when the user provides an issue ID or pastes an issue URL (`/error-tracking/<id>`) and wants to understand the error — who it affects, what triggers it, when it started, whether it correlates with a release, browser, OS, or feature flag, and what the next step should be. Pulls aggregated metrics, sample exception events, segment breakdowns, linked replays, and synthesizes a hypothesis-grade summary in one pass.
Investigate logs in a PostHog project: verify a service or deployment is healthy, explain an error spike, triage an incident, or understand what a log stream is saying. Use when the user asks to "check the logs", asks whether a service, deploy, release, or change is working or broke anything, asks why errors are up or what changed, or wants the root cause of failures visible in logs. Routes the logs MCP tools (services overview, pattern mining, before/after pattern diffing, bucketed counts, facets, raw rows) so investigations start from summaries instead of raw rows or hand-written SQL over the logs table.
Investigates server/infrastructure metric anomalies in PostHog Metrics — from "this metric is rising/dropping/spiking" or a fired alert to a probable cause with evidence. Use when asked why a metric looks wrong (ingestion lag rising, error rate spiking, latency degrading, queue depth growing, throughput dropping), when an alert fires on an OTel/Prometheus metric, or for any incident triage that starts from a metric symptom. Composes characterize-metric-anomaly, query-metrics, and metric-names-list with logs (query-logs) and traces (APM span tools) for cross-signal root-cause correlation.
PostHog LLM analytics for all supported providers
PostHog logs for Datadog
PostHog logs for Go
PostHog logs for Java
PostHog logs for Next.js
PostHog logs for Node.js
PostHog logs for Other Languages
PostHog logs for Python
Create and manage PostHog reminders — private, human-paced nudges that fire as in-app notifications on a schedule, optionally linked to a PostHog resource. Use when the user says "remind me to…", wants a one-off or recurring nudge (daily/weekly/monthly/yearly, a cron schedule, or a specific date/time), wants to be reminded to look at a dashboard, insight, experiment, feature flag, survey, notebook, replay, or error, or wants to list, change, or cancel their reminders. Covers when to pick a reminder over an alert or subscription, the one-off vs recurring vs cron schedule field mappings, timezones, and attaching a resource.
Create, deploy, and operate Streamlit apps in PostHog via the streamlit-apps MCP tools — create an app, set its source, read and patch its code, start and stop its sandbox, poll status, list versions, delete, and share the app with humans via its PostHog URL. Use when asked to "create a streamlit app", "deploy a data app", "ship a dashboard app", "restart/stop my app", "why is my app not running", or "give me a link to the app".
Create and manage scheduled PostHog subscriptions for insight snapshots, dashboard snapshots, and AI prompt reports. Use when a user wants recurring email, Slack, or Microsoft Teams delivery; an AI summary; delivery history; schedule or recipient changes; a test delivery; pause, resume, or deletion; or help with subscription permissions, limits, billing, and failures. Use product alerts when delivery must depend on a threshold or anomaly.
Build reusable activation models — an activation-rate metric and a per-user/per-account activated flag — on either PostHog data-warehouse views (HogQL) or an external dbt project. Use when the user wants to define, model, or measure activation, the "aha moment", onboarding success, or which early actions predict a user sticking around. The core idea this skill enforces: activation is NOT a single assumed event — it is a retention-validated combination of early actions, chosen by balancing reach (enough users hit it) against predictive power (those who hit it retain much better). Covers finding candidate actions, validating them against retention lift, count thresholds and action combinations, per-product and B2B group-level activation, and modeling the winning definition as a durable activated-flag + activation-rate model. Read modeling-warehouse-foundations first; composes modeling-product-usage-metrics for the retention validation.
Build reusable conversion models — funnel/step conversion rates, drop-off, and time-to-convert — on either PostHog data-warehouse views (HogQL) or an external dbt project. Use when the user wants to model, define, or compute a conversion rate, funnel, step completion, drop-off, activation-funnel, signup-to-paid, or any "what % of users who did A went on to do B (within N days)" metric. Covers the funnel model (ordered steps, the conversion-window time-box, strict vs any-order), the person-vs-group aggregation unit, overall vs step-to-step conversion (two different numbers), breakdown attribution, and when a saved funnel insight beats a warehouse view. On PostHog, model funnels in HogQL with windowFunnel; in dbt, stage the event stream and compute an fct_conversion mart with tests. Read modeling-warehouse-foundations first for the view-vs-dbt mechanics; pairs with query-funnel for interactive analysis.
Build reusable dimension / lookup tables for a star schema — country/region, timezone, currency, date, plan/product, and other descriptive attributes — on either PostHog data-warehouse views (HogQL) or an external dbt project. Use when the user wants to model dimension tables, lookup tables, a star schema, conformed dimensions, or wants to enrich events/revenue/usage with country, region, timezone, plan, or currency attributes without repeating JOINs. Covers sourcing the dimension data (upload, warehouse source, or derive from events), shaping it into an aliased one-row-per-entity view (optionally materialized on a slow schedule since dimensions change rarely), and attaching it to facts via a saved or person join so its columns read as native fields. Key rule: for currency use the built-in convertCurrency() instead of a hand-rolled rate table. Read modeling-warehouse-foundations first; dimensions here are reused by the revenue, conversion, activation, and product-usage modeling skills.
Build reusable product-usage and engagement models — retention, stickiness, and lifecycle — on either PostHog data-warehouse views (HogQL) or an external dbt project. Use when the user wants to model, define, or compute whether users come back (retention / churn), how frequently they engage (stickiness / power users / DAU-WAU-MAU ratio), or the composition of the active base (new / returning / resurrecting / dormant lifecycle). These three are one engagement family sharing a start-event/return-event vocabulary and an interval granularity; this skill treats them together and helps pick the right lens: retention for the return-rate cohort matrix, stickiness for the frequency distribution, lifecycle for growth quality. On PostHog, model them in HogQL (mirroring query-retention / query-stickiness / query-lifecycle); in dbt, build fct_retention / fct_stickiness / fct_lifecycle marts with tests. Read modeling-warehouse-foundations first; feeds the retention validation used by modeling-activation-metrics.
Build reusable revenue models — MRR, ARR, gross revenue, new/expansion/contraction/churn, ARPU, LTV, and per-customer/per-account revenue — on either PostHog data-warehouse views (HogQL) or an external dbt project. Use when the user wants to model, define, or compute recurring revenue, monthly/annual recurring revenue, churn or retention of revenue, lifetime value, average revenue per user, or revenue by customer, cohort, product, or currency. On PostHog, build on the managed *_revenue_view views (revenue_item, mrr, customer, subscription, charge, product) fed by Stripe or custom revenue events — not raw Stripe tables — and normalize money with convertCurrency(). In dbt, stage the payment source and compute fct_mrr / fct_revenue_item / dim_customer marts with tests. Covers picking the right source, the subscription-config gotcha that leaves MRR empty, currency handling, and linking revenue to persons/groups. Read modeling-warehouse-foundations first for the view-vs-dbt mechanics.
Shared foundations for building reusable data models in PostHog, on either of two stacks: PostHog-native data-warehouse views / materialized views (HogQL, via the view-* MCP tools), or an external dbt project (sources.yml + staging/marts + schema tests) run against your own or PostHog's managed warehouse. Read before authoring any specific business model — covers the PostHog-vs-dbt decision, the view-create → view-materialize → sync_frequency workflow and the HogQL column-aliasing rule, the dbt project skeleton and the honest "no native dbt integration" picture, warehouse joins and star-schema dimensions, currency conversion with convertCurrency(), and checking/registering models in the data catalog for reuse. Companion to the domain skills modeling-revenue-metrics, modeling-conversion-metrics, modeling-activation-metrics, modeling-product-usage-metrics, and modeling-dimension-tables. Use when the user asks how to build a view, materialized view, or dbt model in PostHog, or which of the two stacks to use.
Build the case for converting a PostHog monthly/PAYG customer to an annual prepaid credit plan. Pulls 12-24 months of invoice history from the data warehouse, runs the handbook eligibility check, projects forward growth, applies the handbook discount tiers, scans recent customer touchpoints (Slack, Gmail, Granola) for confounding variables, fetches customer momentum signals via Exa, emulates the rep's own writing voice, and emits a succinct briefing plus a plain-text Slack draft. Trigger on "annual conversion math for [account]", "monthly to annual for [account]", "draft annual nudge for [account]", or "credit-discount math for [account]".
Add PostHog error tracking to capture and monitor exceptions. Use after implementing features or reviewing PRs to ensure errors are tracked with stack traces and source maps. Also handles initial PostHog SDK setup if not yet installed.
Add PostHog feature flags to gate new functionality. Use after implementing features or reviewing PRs to ensure safe rollouts with feature flag controls. Also handles initial PostHog SDK setup if not yet installed.
Add PostHog SDK integration to your application. Use when setting up PostHog for the first time or reviewing PRs that need PostHog initialization. Covers SDK installation, provider setup, and basic configuration for any framework.
Add PostHog LLM analytics to trace AI model usage. Use after implementing LLM features or reviewing PRs to ensure all generations are captured with token counts, latency, and costs. Also handles initial PostHog SDK setup if not yet installed.
Add PostHog log capture to track application logs. Use after implementing features or reviewing PRs to ensure meaningful log events are captured with structured properties. Also handles initial OTLP exporter setup if not yet configured.
Add PostHog product analytics events to track user behavior. Use after implementing new features or reviewing PRs to ensure meaningful user actions are captured. Also handles initial PostHog SDK setup if not yet installed.
Plan a round of user interviews conducted by PostHog''s AI voice agent (a "robo interviewer") — the automated voice-agent interview product. Captures a UserInterviewTopic (who to target, what to ask, framing context, question list) and calls user-interview-topics-create. ONLY trigger when the user clearly wants an AI voice agent to actually run the interview calls (e.g. "set up robo user interviews", "have the voice agent interview these users"). Do NOT trigger for ordinary user research that does not involve the voice agent — finding or shortlisting users to talk to ("who''d be a good fit to interview about Y"), planning questions for a human-run interview, or analysing feedback are audience discovery, handled with normal data queries, not this skill. Also do NOT trigger for uploading a recorded interview audio file or browsing topics with user-interview-topics-list. When intent is ambiguous, first confirm what kind of research it is and whether they want an AI voice agent to conduct it (see Step 0).
Use before emailing a PostHog customer, replying to one, or joining a call, and for any request to research a PostHog account. Fires on "/posthog-customer-deep-dive" and on natural language like "deep dive on X", "look up this customer", "help me reply to Y", "prep me for my call with Z", from an email address, domain, account name, PostHog org id, or Customer Analytics account id. Researches the account across Customer Analytics, the onboarding model and its Onboarding:: workflows, the email sync, and project 2 usage and billing queries, then drafts an email (first touch, follow-up, or reply) or a call-prep brief, every recommendation carrying a live docs link.
Debug and inspect PostHog implementations on any website. Use this skill when a user wants to understand how PostHog is implemented on a page, troubleshoot tracking issues, verify configuration, check what events are being sent, or audit a PostHog setup. Works with Chrome DevTools MCP and Playwright MCP to inspect live websites.
Evaluate and respond to inbound PostHog sales leads from Salesforce. Use this skill when any PostHog TAE needs to triage an inbound lead — deciding whether to qualify for a call, route to self-serve, or disqualify — and then draft an appropriate response email. Checks Vitally for existing account context before qualifying. Triggers on "respond to this lead", "triage this inbound", "write a response to this lead", "disposition this lead", "evaluate this Salesforce lead", or any request involving an inbound sales inquiry that needs qualification and a reply. Also trigger when a TAE pastes or describes lead details and asks what to do with them.
Help existing PostHog customers improve their PostHog instance. Triggers on "help [customer] improve their PostHog setup", "audit [company]'s PostHog instance", "create tracking plan for [company]", "design data schema for [customer]", or requests to improve analytics coverage, fix instrumentation gaps, expand PostHog usage, or build better insights for customers already using PostHog. Use when working with a customer who already has PostHog installed.
Research and qualify onboarding team referral leads for PostHog. Use this skill when a TAE receives a lead from the onboarding team and needs a full research brief before deciding how to engage. Triggers on 'research this onboarding lead', 'onboarding team referred [company]', 'look into [company] from onboarding', 'qualify this onboarding referral', 'what do we know about [company] from onboarding', or any request to research a company that came through the onboarding pipeline. Also trigger when a TAE pastes a company name and mentions it's from the onboarding team, or says something like 'onboarding sent me [company]', 'got a handoff for [company]', or '[name] from onboarding sent me [company]'. This skill does deep research and qualification, then drafts outreach when the recommendation is to engage.
Research, qualify, and suggest outreach for PostHog big fish product-led leads — large companies (500+ or 1000+ employees) using PostHog on free tier without a payment method. Use this skill when a TAE needs to work a big fish alert from Salesforce. Triggers on 'work this big fish lead', 'research this product-led lead', 'big fish alert', '500+ employees no payment method', '1000+ employees no payment method', or any request involving a large-company product-led lead that needs research, qualification, and an outreach recommendation. Also trigger when a TAE pastes Salesforce lead details with matching criteria like 'Big fish alert' or '500+ employees, no payment method'.
Qualify and draft outreach for PostHog product-led leads who are hitting a billing transition — either startup program customers rolling off free credits, or users whose first invoice will be >= $2K. Use this skill when a TAE needs to work a startup rolloff lead, a high first-invoice alert, or any lead where the matching criteria mentions 'startup rolloff', 'credit spend', 'first invoice', 'credits expiring', or 'high usage transition'. Also trigger when a TAE pastes Salesforce lead details with matching criteria like 'Startup rolloff + high credit spend' or 'First invoice >= $2K'.
Create and configure surveys in PostHog through guided conversation. Use this skill when a user wants to create a survey, collect user feedback, run NPS/CSAT/CES/PMF surveys, gather product feedback, or understand user sentiment. The skill guides Product Managers through survey design by matching their goals to proven templates (or creating custom surveys), then configuring targeting and scheduling before creating via PostHog MCP tools.
Get PostHog data into a canvas correctly: the host-injected `ph` SDK (loadInsight, query, capture, state, connectors, openExternal, navigate), the data hierarchy (saved insights first, typed query nodes second, inline HogQL last), verifiability (insight-backed metrics link their saved insight in PostHog; ad-hoc queries expose the exact query that ran), per-insight-type result shapes, progressive per-query loading, date-range wiring, live third-party data through the viewer's own connections (ph.connectors), and event capture from a canvas. Use whenever a canvas shows metrics, charts, tables, any PostHog data, or data from GitHub or an MCP server, or needs to send analytics events.
Explains how to query PostHog data, defaulting to typed runners for supported product analytics. Read it before you write HogQL/SQL. Also read it before you call execute-sql against PostHog. Use it to find or aggregate PostHog entities. These entities include insights, dashboards, cohorts, feature flags, experiments, surveys, hog flows, warehouse data, and persons. Use it for trends, funnels, retention, lifecycle, paths, stickiness, web analytics, error tracking, logs, sessions, and LLM traces. Before you calculate a governed business or telemetry measure, check system.information_schema.metrics for an approved definition. Examples include MRR, activation, billable usage, active organizations, and failure rates. Use the approved definition before you derive a measure from raw events or use a typed domain tool. It also covers HogQL differences, system table schemas, functions, query examples, and schema discovery.
Diagnoses and resolves PostHog ingestion warnings — problems recorded while ingesting events (dropped events, rejected person merges, oversized payloads, invalid data). Use when a user asks why events are missing, dropped, or undercounted, why identify/alias calls don't work or accounts stay duplicated, why person or group properties aren't updating or profiles look inflated, why recordings have gaps, heatmaps are empty, LLM token counts are missing, why cookieless events vanish, or whenever the `ingestion_warning` health check fires. Explains severity triage (error = dropped, warning = modified, info = intentional) and routes all warning types — size limits and enrichment, merges and distinct IDs, high-volume distinct IDs, `$process_person_profile`, timestamps, cookieless, heatmaps, transformations, session replay — to per-issue reference files with code-level causes and per-SDK fixes.
How to author custom PostHog Review skills: the review perspectives, blind-spot checks, validation criteria, and resolution criteria that drive PostHog Review's automated PR reviews. Use when a user wants a new review perspective (a specialist lens on their PRs), a custom blind-spot sweep, their own validation bar for which findings get published, or their own bar for which review comments get implemented. Trigger on "create a PostHog Review perspective", "custom review perspective", "my own blind-spot check", "custom validation criteria", "custom resolution criteria", "tune what PostHog Review publishes", "tune what PostHog Review implements".
Checks each chunk for issues the other reviewers missed. Uses their findings to avoid repeating them.
Checks security, input validation, and API compatibility. Reports security and contract issues only.
Checks business logic, edge cases, data transformations, and queries. Reports correctness issues only.
Checks resource use, error recovery, and scaling. Reports performance and reliability issues only.
Implements safe, verifiable fixes from review comments. Explains declined requests and asks a human to handle risky changes.
Keeps findings that affect correctness, security, data, API compatibility, or performance. Drops speculative issues and style suggestions before publishing.
Connect an arbitrary REST API to the PostHog data warehouse as a Custom source by authoring a JSON manifest, with no per-source code. Use when the user points at an API that has no built-in PostHog connector — "import data from this REST API", "sync my internal API", "connect this API from its docs", "build a custom data warehouse source" — and gives a docs URL or a natural-language description of the endpoints. Walks through drafting the RESTAPIConfig manifest (auth — bearer, API key, HTTP basic, or OAuth2 client credentials / refresh token — pagination, record path, incremental cursor, parent/child fan-out), validating it, test-reading live rows to verify the field mappings, and creating the source. If the API already has a native PostHog connector, use setting-up-a-data-warehouse-source instead — this skill checks the connector registry first and only handles APIs with no native connector.
Populate person or group properties from a data warehouse table or materialized view, so warehouse columns become properties usable in feature flags, cohorts, and insights. Use when the user wants to "sync my Postgres columns to person properties", "map a warehouse table to people", "replace our daily identify cron", "update person properties from the warehouse", or asks for reverse ETL into PostHog. Covers picking the table and the identifier column, proposing a whole-table column mapping in one call, excluding identity and reserved properties, checking collisions with properties that already exist, and running the first backfill.
Signals scout for PostHog AI observability. Watches LLM traces for cost, latency, error, volume, and eval-performance regressions.
Signals scout for PostHog distributed tracing (APM / OpenTelemetry spans). Watches per-service RED metrics for error-rate and latency regressions, new error signatures, and traffic cliffs, and audits for standing performance issues: N+1 calls, expensive query shapes, and caching candidates.
Signals scout for PostHog Conversations (support inbox). Watches `$conversation_*` ticket- lifecycle events for SLA breach steps, first-response latency blowouts, backlog imbalance, and channel or assignment concentration.
Signals scout for PostHog Customer analytics (Accounts). Watches per-account engagement for churn-risk shapes — engagement cliffs, dormancy, champion departure — and the expansion inverse.
Signals scout for PostHog data pipelines — CDP destinations and transformations, batch exports, and hog flows. Watches for delivery failures, degraded functions, and stalled exports against each pipeline's baseline.
Signals scout for PostHog error tracking. Watches `$exception` bursts, stuck loops, multi- fingerprint clusters, and status regressions.
Signals scout for PostHog A/B experiments. Watches running experiments for validity threats — sample ratio mismatch, contamination, exposure stalls, mid-run flag mutations — and lifecycle drift.
Signals scout for PostHog feature flags. Watches the flag roster and the `$feature_flag_called` stream for evaluation cliffs, ghost flags, response-distribution shifts, and flag debt.
Signals scout over PostHog's own health checks. Bundles the project's active health issues by kind, weights them by blast radius, and surfaces the ones worth acting on.
Signals scout for PostHog logs. Watches for emerging and rate-shifted message patterns, volume bursts, severity-distribution shifts, service silence, and trace-correlated bursts.
Signals scout for PostHog MCP tool calls. Watches `$mcp_tool_call` telemetry for tools that need improvement — broad-reach failure rates, retry hammering, slow or context-bloating responses — grouped by owning product category, each with a fix suggestion.
Signals scout for PostHog Replay Vision scanners. Watches that enabled scanners keep observing (throughput and quota cliffs) and that aggregate score shifts and recurring themes get surfaced.
Signals scout for PostHog revenue analytics. Watches for upstream failures (Stripe sync stalls, capture regressions), and config drift.
Signals scout for PostHog session replay. Watches that sessions keep recording (capture cliffs) and surfaces friction inside recordings — rage/dead-click clusters, error-after- interaction cohorts.
Skill-hygiene scout for the team's PostHog skills store. Watches recently-changed and most- used skills for authoring violations — vague descriptions, bloated bodies, dead file links, kitchen-sink scope, committed secrets.
Signals scout for PostHog surveys. Watches active surveys for score regressions, response- volume drops, abandonment spikes, and targeting drift, and aggregates open-text responses into recurring themes.
Signals scout for PostHog Tasks. Watches delivery health — failing runs clustered by repository and error class, retry storms — and, on a slower rotation, recurring demand across human-authored tasks. Skips the scout fleet's own runs.
Signals scout for PostHog web traffic. Watches per-channel session volume, attribution breakage, and landing-page health (bounce and 404 steps) against the site's own baseline. Per- page web vitals belong to `signals-scout-web-vitals`.
Discover and use shared team skills stored in PostHog. Use when the user asks to list, browse, load, or manage "shared skills", "team skills", or references the "skills store" / "skill store".
Use when the user asks about revenue, payments, subscriptions, billing, CRM deals, support tickets, ad spend, production database tables, or other data PostHog does not collect natively — or wants to join or correlate PostHog product events with that external business data. Also use when a query fails because a table does not exist or returns no results for expected external data. The data warehouse can import from SaaS tools (Stripe, Hubspot, Zendesk, etc.), ad platforms, production databases (Postgres, MySQL, BigQuery, Snowflake), and other arbitrary data sources. Covers checking existing sources, identifying the right source type, and guiding the setup.
Create PostHog error tracking suppression rules to drop high-volume, low-value errors at ingestion. Use when the user asks "stop capturing this error", "drop browser extension errors", "ignore ResizeObserver loops", "suppress bot-driven errors", or wants to reduce ingestion cost from noisy unactionable errors. Identifies suppression candidates, scopes the filter tightly, decides between full suppression and sampling, and confirms the rule before creating it. Suppressed errors are dropped permanently — this skill defaults to caution.
HogQL queries for PostHog analytics
Triage PostHog error tracking issues during a daily or on-call review. Use when the user asks "what's broken?", "what new errors do we have?", "show me top errors today", "what should I look at this morning", or wants a prioritized list of active issues to work on. Surfaces new and high-impact issues, ranks by users affected and recency, points at linked replays, and proposes next actions (investigate, assign, suppress, merge).
Inspects PostHog Visual Review (VR) runs that gate PR merges with screenshot regression checks. Use when the user mentions "visual review", "VR", "snapshot diff", "screenshot test", "storybook regression", "playwright snapshot", "quarantine", asks why a PR is blocked or what changed visually, wants to triage the VR backlog, decide whether a snapshot diff is real vs flaky, quarantine or lift a flaky story, or check whether a story has been changing across runs. Also invoke when a PR has a failing `visual-review` status check, when a PR comment mentions "Visual review", when a PR from a fork fails `Visual regression tests pass`, or when the user is on a branch with an open VR run.
Converts engineering analytics (PR / CI) data into saved PostHog insights, dashboards, and subscriptions, and explains how to query the product data directly with SQL. Covers discovering per-team GitHub warehouse tables via engineering-analytics-sources, replicating curated column semantics in HogQL, reading exposed engineering_analytics_* warehouse views where product logic is involved (CI cost, fingerprinted failure lines, commit attribution), saving queries with insight-create, and scheduling delivery with subscriptions-create. Use when asked to "save this as an insight", "put CI health / merge times on a dashboard", "email me PR throughput weekly", "chart CI cost", "track time to first review", "subscribe to these numbers", "alert on CI success rate", or "what data/tables/views does engineering analytics read". For ad-hoc CI and merge questions use diagnosing-ci-and-merge-bottlenecks; to investigate one specific CI failure use investigating-ci-failures.
Explains PostHog billing usage and spend from the customer's visible Billing MCP tools. Use when the user asks why usage or spend is high, which product or project is driving usage, what a usage type means, how to reduce usage, what changed over time, why they got a usage change alert, or whether a spike/drop alert was real or noisy. Also use before product-specific analytics skills when the user names a billable PostHog product metric such as events, recordings, feature flag requests, exceptions, survey responses, synced rows, logs, AI events, AI credits, or Inbox credits. Starts from Billing usage/spend tools, then routes to customer-visible product MCP surfaces for deeper investigation.
Deep dive on a PostHog user by email address. Analyze what they do, where they spend time, and what products they use.
Work with PostHog Signals scouts: scheduled agents that monitor a project and write reports into the Signals inbox. Use to assign monitoring work, schedule quality scoring, find which scout covers a surface, act on reports, reduce noise, investigate missing findings, or improve the fleet through feedback and calibration. Also covers follow-up checks that verify whether a reported problem stays fixed. Use `authoring-scouts` for edits, `exploring-scouts` for run observability, and `inbox-exploration` for report triage. Trigger on "work with my scouts", "get more out of scouts", "have a scout watch X", "tell me if Y spikes", "score X on a schedule", "measure quality of Y", "what do I do with this scout report", "calibrate/review my scout fleet".
Best practices for agents managing PostHog skills via the MCP `skill-*` tools — how to discover, read, create, update, and refactor skills efficiently, especially large skills with many bundled files. Use whenever you are about to call any `skill-*` tool, asked to author or edit a shared skill, or troubleshoot why a skill write was rejected. Also use when asked what skills are good for or how to shape one (project hub, runbook, catalog, handover, daily driver). Pairs with `skills-store` (which covers the raw tool surface) by adding the decision-tree, efficiency, pattern, and pitfall guidance.
Read and use comments attached to the current PostHog task, its artifacts, and any canvas through the PostHog MCP exec dispatcher. Use when the user mentions task comments, artifact or canvas comments, annotations, selected-text feedback, replies, unresolved comments, or asks an agent to inspect or act on feedback left in PostHog Desktop. Covers exec discovery and calls, target filtering, pagination, full-thread retrieval, anchor/version context, task-scoped access, and standalone canvas comments that have no task.
Generate comprehensive workload analysis visualizations for PostHog customer accounts. Use when user requests account analysis, workload breakdown, SDK analysis, spend allocation, or expansion opportunity assessment. Triggers include "analyze [account]", "workload analysis for [account]", "SDK breakdown for [account]", "show me how [account] uses PostHog", or any request to understand customer usage patterns across products and platforms.
Write Streamlit app source code that runs well in a PostHog sandbox — the posthog_apps.query() bridge for reading PostHog data, the packages baked into the sandbox image, caching and session state across Streamlit reruns, layout and chart patterns, and the app.py entry point with any helper modules and data files bundled beside it. Use when authoring or debugging the Python source of a PostHog Streamlit app, when a query inside an app fails, or when asked to "write a streamlit app that shows PostHog data".
Iris is Redis's umbrella for AI-focused products. Use this skill when integrating with the Iris Redis Agent Memory (RAM) data plane on Redis Cloud — recording session events for an AI agent, creating or searching long-term memories, configuring a memory store, or tuning background memory promotion. Code examples use the official `redis-agent-memory` (Python) and `@redis-iris/agent-memory` (TypeScript) SDKs.
Redis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROSSSLOT errors, and reading from replicas to scale read-heavy workloads. Use when designing keys for a sharded Redis Cluster, debugging CROSSSLOT errors on MGET / SDIFF / pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.
Redis client and connection guidance covering connection pooling, multiplexing, pipelining, client-side caching with RESP3, avoiding slow commands (KEYS, SMEMBERS, HGETALL), and tuning socket timeouts. Use when configuring a Redis client (redis-py, Jedis, Lettuce, NRedisStack), batching commands for throughput, eliminating per-request connection creation, iterating large keyspaces with SCAN, enabling client-side caching for read-heavy workloads, or setting connect and read timeouts.
Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing/cleaning up Redis key naming.
Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.
Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, JSON path), DIALECT 2 query syntax, FT.SEARCH / FT.AGGREGATE / FT.HYBRID command selection, vector similarity with HNSW or FLAT, hybrid retrieval combining lexical and vector ranking, RAG pipelines, zero-downtime index updates via aliases, and debugging with FT.PROFILE and FT.EXPLAIN. Use when defining a search index on Hash or JSON documents, writing FT.SEARCH queries with filters, sorting, aggregation, or vector KNN, tuning HNSW parameters, building a RAG retrieval pipeline, or troubleshooting slow or empty search results.
Redis security guidance covering authentication (requirepass and ACL users), TLS, ACL-based least-privilege access control, restricting network exposure via bind and protected-mode, firewall rules, and disabling dangerous commands. Use when deploying Redis to production, defining ACL users for an application, configuring TLS connections, locking down a Redis instance behind a firewall, or auditing a Redis deployment for security hardening.
Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.
Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).
Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.
Set up Temporal Cloud and run a sample Workflow on it for the user, doing the work end to end. Use when the user wants to set up Temporal Cloud, get started on Temporal Cloud, install the unified Temporal CLI (prerelease cloud-cli), create a Cloud namespace or API key, clone a money-transfer sample app, write the client config TOML, or connect a local Worker to Temporal Cloud and run a sample Workflow. This is the Cloud setup path, not the local learning path (see temporal-getting-started). Covers Python, TypeScript, Go, Java, .NET, and Ruby SDKs.
Develop, debug, and manage Temporal applications across Python, TypeScript, Go, Java, .NET, Ruby, and Rust. Use when the user is building workflows, activities, workers, or background job queues with a Temporal SDK, debugging issues like non-determinism errors, stuck workflows, or activity retries, using Temporal CLI, Temporal Server, or Temporal Cloud, or working with durable execution concepts like signals, queries, heartbeats, versioning, continue-as-new, child workflows, or saga patterns. Also use when the user mentions "run a Temporal workflow from the CLI", "start a dev server", "run temporal server start-dev", "temporal workflow start", "temporal workflow execute", "temporal workflow signal", "temporal workflow query", "temporal workflow update".
Administer and diagnose running Temporal Cloud or self-hosted Temporal Server environments via CLI (temporal, tcld) — not SDK code. Operations: namespace CRUD, Cloud capacity/APS, API-key rotation, mTLS cert rotation, workflow health, batch cancel/terminate/reset, export, search attributes, Ops API, billing, audit logs, Terraform, SAML/SCIM, migration. Diagnosis: bottom-up triage of stuck workflows, non-determinism, worker-health, task-queue problems, HA failover, payload size limits, performance bottlenecks, missed schedules. Do NOT trigger for generic TLS/gRPC errors unrelated to Temporal, writing application code (temporal-developer), or worker tuning/sizing (temporal-workertuning).
Deploy and operate Temporal Workers on serverless compute (AWS Lambda, GCP Cloud Run) driven by the Worker Controller Instance (WCI). Use when the user mentions: "serverless worker", "Temporal serverless", "Worker Controller Instance", "WCI", "deploy Temporal worker on Lambda", "Lambda packaging", "Lambda timeout", "WCI inspection", "CloudFormation Temporal", "Cloud Run worker", "deploy Temporal worker on Cloud Run".
3,022 skills from 132 repositories across 132 publishers, each read from the SKILL.md that defines it.
Other indexes list far more. The largest we checked carried 7,845 skills on 16 September 2026, including 542 under “anthropic” where the official repository holds 20. We publish what resolves to a file we actually read, with that file’s own URL beside it — a shorter list every row of which can be checked.
The rest of the gap is ours, not theirs: 65 of the 209 publishers we know of resolve to no repository we can find — the name is not a GitHub organisation, and a search does not place it. Those are skills that may well exist and that we cannot yet read, which is a different thing from skills we chose to leave out.
For a model reading this page
Plain text, same figures, no markup: /resources/skills/llms.txt.