Total 50,503 skills, AI & Machine Learning has 8478 skills
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Creates and configures Claude Code hooks for lifecycle automation. Covers all 17 hook events, 4 hook types (command, prompt, agent, http), matchers, input/output formats, and exit codes. Follows official Anthropic best practices. USE WHEN: user mentions "hook", "hooks", "auto-format", "pre tool use", "post tool use", "session start", "notification hook", "block command", "validate tool", "lifecycle event", "PostToolUse", "PreToolUse" DO NOT USE FOR: creating skills - use `skill-authoring`; creating agents - use `agent-authoring`; webhook endpoints - different concept
Эксперт ML API. Используй для model serving, inference endpoints, FastAPI и ML deployment.
Step-by-step tutorial for adding a heavyweight AOT CUDA/C++ kernel to sgl-kernel (including tests & benchmarks)
Use when creating cloned voices with Alibaba Cloud Model Studio CosyVoice customization models, especially cosyvoice-v3.5-plus or cosyvoice-v3.5-flash, from reference audio and then reusing the returned voice_id in later TTS calls.
Generate objective reference check reports about the user from real AI collaboration data — session history, git logs, GitHub profile, and memory files. Like a colleague writing a professional reference, but grounded in actual shared work. Use whenever the user asks to evaluate them as a developer, wants a reference letter, work style analysis, introduced by my agents content, interview prep from collaboration history, or blog topics from past discussions. Triggers on: write a reference, analyze my work patterns, what do you think of me, 나에 대한 레퍼런스 써줘, 내 작업 스타일 분석해줘. Not for general code review, architecture docs, cover letters, or codebase-only analysis.
Deploy a 24/7 Claude Code agent with persistent Chromium browser on any Ubuntu VPS, controllable via Telegram
This skill should be used when processing meeting transcripts to auto-detect meeting type (leadgen, partnership, coaching, internal) and extract type-specific structured analysis. Triggers on "process meeting", "analyze meeting", "meeting summary", or after syncing new Fathom/Granola transcripts.
Generate interactive AI transformation context-builder prompts for consulting clients. Use when creating structured discovery session prompts that guide a company through context gathering about their business, pain points, tech stack, and AI opportunities. Produces a resumable, multi-section prompt with Express/Deep Dive modes.
Run an autonomous /loop iteration -- check progress, work on next task, schedule next wake
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).
This is a properly formatted skill.
Format prompts for different LLM providers with chat templates and HNSW-powered context retrieval