发现 tools llm ai 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
Use this agent when you need to analyze code for performance issues, optimize algorithms, identify bottlenecks, or ensure scalability. This includes reviewing database queries, memory usage, caching strategies,...
Expert guidance for creating, writing, and refining Antigravity Skills. Use when working with SKILL.md files, authoring new skills, improving existing skills, or understanding skill structure and best practices...
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 Antigravity's capabilities with specialized knowledge, workflows,...
Use this agent when you need to research and gather external best practices, documentation, and examples for any technology, framework, or development practice. This includes finding official documentation, com...
Personalized coding tutorials that build on your existing knowledge and use your actual codebase for examples. Creates a persistent learning trail that compounds over time using the power of AI, spaced repetiti...
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes a...
This skill should be used when working with DSPy.rb, a Ruby framework for building type-safe, composable LLM applications. Use this when implementing predictable AI features, creating LLM signatures and modules...
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...
Guide for Claude Code skills installation, usage, and development. Use when working with Claude Code specific features, paths, and conventions.
Guide for AI Agents and LLM development skills including RAG, multi-agent systems, prompt engineering, memory systems, and context engineering.
Guide for creating Agent Skills: structure, best practices, and SKILL.md format for Claude Code, Codex, Gemini CLI, and other AI agents.
Guide for multi-platform skill compatibility across Claude Code, Codex, Gemini CLI, Cursor, GitHub Copilot, and other AI coding agents.
Guide for LLM security attacks: prompt injection, jailbreaking, data extraction, and where to place resources in README.md.
Centralized AI-readable documentation repository with 245+ frameworks and tools. Use to find documentation, add new sources, or update existing docs. Located at ~/github/llm-code-docs.
Knowledge for writing effective Claude Code instructions. Auto-triggers for CLAUDE.md, SKILL.md, command files.
Review essential documentation and context at session start. Use when beginning a new session to load AI rules, git state, and pending tasks.
Invoke HISTORIAN for session documentation, historical records, and continuity. Creates human-readable narratives for non-technical stakeholders. Not invoked for routine work - only for poignant, significant se...
Understand agent context isolation and write effective prompts for spawned agents. Use when orchestrating multi-agent workflows to ensure subagents receive complete, self-contained context.
Claude Code ベストプラクティスの対話形式セットアップウィザード。Use PROACTIVELY when setting up new projects, configuring Claude Code, adding agents/rules/hooks, or when user mentions "bootstrap", "setup claude...
Initialize session as ORCHESTRATOR agent with multi-agent coordination capability. Use for complex tasks requiring parallel agent spawning and result synthesis.
Create effective Claude Code custom commands for workflow automation. Use when creating new custom commands, understanding YAML frontmatter structure (description, allowed-tools, argument-hint, model, disable-m...
Create new PAI agents using AGENT_FACTORY.md patterns. Guides through archetype selection (Researcher, Validator, Generator, Critic, Synthesizer), validates against CONSTITUTION.md, and generates agent specific...
Initialize session as ORCHESTRATOR agent with multi-agent coordination capability. Use for complex tasks requiring parallel agent spawning and result synthesis.
Tool discovery, routing, chaining, error handling, and composition for the 34+ MCP scheduling tools. Use when orchestrating complex multi-tool workflows, handling MCP errors, or discovering available capabiliti...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。