Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.
Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.
Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API.
基于RFC驱动的多智能体DAG执行模式，包含质量门、合并队列和工作单元编排。
Scan skills to extract cross-cutting principles and distill them into rules — append, revise, or create new rule files
将纠错经验沉淀为持久化的 Rules/Skills 更新，构建反馈闭环。当被用户纠正且错误具有模式性时自动触发，或通过 /reflect 命令手动触发回顾。
Interactive agent picker for composing and dispatching parallel teams
Deep interview a human and compile them into an installable AI agent plugin. Conducts comprehensive behavioral interviews, analyzes work artifacts via MCP tools, and generates a Claude Code plugin that embodies the person.