Browse skills

Use the ClawHub CLI to search, install, update, and publish agent skills from clawhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawhub CLI.

Delegate coding tasks to Codex, Claude Code, or Pi agents via background process. Use when: (1) building/creating new features or apps, (2) reviewing PRs (spawn in temp dir), (3) refactoring large codebases, (4) iterative coding that needs file exploration. NOT for: simple one-liner fixes (just edit), reading code (use read tool), thread-bound ACP harness requests in chat (for example spawn/run Codex or Claude Code in a Discord thread; use sessions_spawn with runtime:"acp"), or any work in ~/clawd workspace (never spawn agents here). Requires a bash tool that supports pty:true.

Fetch GitHub issues, spawn sub-agents to implement fixes and open PRs, then monitor and address PR review comments. Usage: /gh-issues [owner/repo] [--label bug] [--limit 5] [--milestone v1.0] [--assignee @me] [--fork user/repo] [--watch] [--interval 5] [--reviews-only] [--cron] [--dry-run] [--model glm-5] [--notify-channel -1002381931352]

Turn this agent into a shareable Claw for a person to review.

Coordinate multi-agent development pipelines using shared JSON task files. Supports Linear, DAG, and Debate modes for AI agent orchestration across code, test, docs, and monitor agents.

Persistent local memory for AI agents. Save, recall, and search project decisions as local JSON. Zero cloud, zero infrastructure — works offline.

Three-layer progressive MCP client with Socket daemon. Query available tools, call MCP servers efficiently, and manage daemon processes. Reduces token overhead with lazy loading.

Full website SEO audit with parallel subagent delegation. Crawls up to 500 pages, detects business type, delegates to 6 specialists, generates health score.

Git Context Controller (GCC) - Manages agent memory as a versioned file system under .GCC/. This skill should be used when working on multi-step projects that benefit from structured memory persistence, milestone tracking, branching for alternative approaches, and cross-session context recovery. Triggers on /gcc commands or natural language like 'commit this progress', 'branch to try an alternative', 'merge results', 'recover context'.

Build agents that generate rich, interactive UIs using Google's A2UI (Agent-to-User Interface) format with Google ADK (Agent Development Kit). Use when building ADK agents that need to render dynamic UI components, forms, cards, lists, or interactive elements via the A2UI declarative JSON format. Includes a Tailwind CSS + shadcn/ui design system flavor for creating beautiful, modern A2UI catalogs and components. Covers A2UI schema management, catalog configuration, A2A transport integration, response parsing/validation, custom catalog creation, and the orchestrator pattern for multi-agent UI routing.

Orchestrate complex development with AUTOMATIC parallel subagent execution, continuous dispatch scheduling, dependency analysis, file conflict detection, and IOSM quality gates. Analyzes task dependencies, builds critical path, launches parallel background workers with lock management, monitors progress, auto-spawns from discoveries. Use for multi-file features, parallel implementation streams, automated task decomposition, brownfield refactoring, or when user mentions "parallel agents", "orchestrate", "swarm", "continuous dispatch", "automatic scheduling", "PRD", "quality gates", "decompose work", "Mixed/brownfield".

Use this skill when designing, generating an MVP blueprint for, auditing, refactoring, or explaining an agentic harness for any domain. Covers provider-neutral agent architecture for OpenAI, Anthropic, and OpenAI-compatible APIs: agent loops, tool design, permissions, system prompts, planning, goals, context compaction, memory, skills, MCP/external connectors, observability, evals, prompt caching, agent-legible environments, feedback loops, and safety.

PavedPath Code is the code-focused edition of PavedPath. It helps agents solve software engineering problems by finding proven implementation paths from GitHub repositories, issues, pull requests, discussions, code examples, release notes, and open-source evidence.

制作哲学、心理、历史、经济、金融与科技等主题的 AI 动画解说视频。适用于 Agent 研究和组织选题、编写旁白、将 1–5 分钟视频拆成均衡的 Seedance 片段、按关键人物数量生成人物参考图、逐片段设计具体场景与多镜头视频提示词、保持旁白音色一致、制作带字封面，或规划基于 CLI 的多模态生成与拼接流程。当前正式维护的执行路径使用 LibTV CLI；查阅最新官方文档后，也可将该生产方法适配到 Higgsfield、即梦及其他同类多模态 CLI。