Total 51,079 skills, AI & Machine Learning has 8556 skills
Showing 12 of 8556 skills
LangChain workflows for `create_agent`, LCEL chains, `bind_tools`, middleware, and structured output with production-safe orchestration. Use when implementing or refactoring LangChain application logic in Python or TypeScript.
The Meta-Skill. Use this to create NEW skills (tools) for the agent.
Use when user has complex multi-agent workflows, needs to coordinate sequential or parallel agent execution, wants workflow visualization and control, or mentions automating repetitive multi-agent processes - guides discovery and usage of the orchestration system
Evaluate how well a codebase supports autonomous AI development. Analyzes repositories across eight technical pillars (Style & Validation, Build System, Testing, Documentation, Dev Environment, Debugging & Observability, Security, Task Discovery) and five maturity levels. Use when users request `/readiness-report` or want to assess agent readiness, codebase maturity, or identify gaps preventing effective AI-assisted development.
Generate production-ready Claude Code hooks with interactive Q&A, automated installation, and enhanced validation. Supports 10 templates across 7 event types for comprehensive workflow automation.
Combine multiple images using Gemini 2.5 Flash (Nano Banana) via OpenRouter. Use when merging 2-8 images with AI-guided composition.
Automatically discover and recommend relevant Claude skills when users encounter tasks that could benefit from specialized capabilities. Use this skill proactively when detecting any of these patterns: (1) User mentions working with specific file formats (PDF, DOCX, Excel, images, etc.), (2) User describes repetitive or specialized tasks (data analysis, code review, deployment, testing, document processing), (3) User asks if there's a tool or capability for something, (4) User struggles with domain-specific work (React development, SQL queries, DevOps, content writing), (5) User mentions needing best practices or patterns for a technology, (6) Any situation where a specialized skill could save time or improve quality. Search using SkillsMP API (if configured), skills.sh leaderboard, or GitHub as fallback. Recommend 1-3 most relevant skills and offer to install via npx skills add.
Guide users through creating high-quality GitHub Copilot prompts with proper structure, tools, and best practices.
Interactive, input-tool powered, task refinement workflow: interrogates scope, deliverables, constraints before carrying out the task; Requires the Joyride extension.
INVOKE THIS SKILL when building ANY retrieval-augmented generation (RAG) system. Covers document loaders, RecursiveCharacterTextSplitter, embeddings (OpenAI), and vector stores (Chroma, FAISS, Pinecone).
Analyzes and refines agent skills by identifying quality issues, prioritizing fixes (MUST/SHOULD/NICE), gathering user feedback, and implementing improvements. Checks for common problems like time estimates, oversized SKILL.md files, poor structure, redundant content, missing examples, and unclear workflows. Use when reviewing, improving, refactoring, or auditing existing skills. Triggers include "review skill", "improve skill", "refactor skill", "skill quality", "audit skill", "fix skill", "optimize skill", "analyze skill".
Optimize, rewrite, and evaluate prompts using the Anthropic 1P interactive prompt-engineering tutorial patterns (clear/direct instructions, role prompting, XML-tag separation, output formatting + prefilling, step-by-step “precognition”, few-shot examples, hallucination reduction, complex prompt templates, prompt chaining, and tool-use XML formats). Use for 提示词优化/Prompt优化/Prompt engineering, rewriting system+user prompts, enforcing structured outputs (XML/JSON), reducing hallucinations, building multi-step prompt templates, adding few-shot examples, or designing prompt-chaining/tool-calling scaffolds.