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Found 1,147 Skills
Curated collection of 1209+ best OpenClaw AI agent skills, weekly updated by MyClaw.ai
Self-referential self-improving AI agents that optimize for any computable task using meta-learning and code generation
Use when scaffolding a new repository (public or private) to the Patina Project baseline, when realigning an existing repository with that baseline, or when auditing or adding commit conventions, PR templates, husky + commitlint, PNPM tooling, release-please, agent docs (AGENTS.md, CLAUDE.md), or AI agent plugin manifests for Claude Code, Codex, Cursor, Windsurf, and Copilot. Triggers on phrases like "scaffold this repo", "scaffold a Patina plugin", "realign with the baseline", "audit our repo conventions", "set up commitlint and husky", or "add Codex/Cursor/Windsurf surfaces".
Run a repo-wide cross-cutting governance audit via the pm-skill-auditor sub-agent. Dispatches natively on Claude Code with the pm-skills plugin (invokes @agent-pm-skill-auditor); on non-Claude clients (Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI) reads subagents/pm-skill-auditor.md and executes the system prompt inline. Returns a layered audit report (full findings + Status Summary prose + Status YAML envelope per master plan D26) with cross-cutting findings graded P0/P1/P2/P3 plus aggregate counter audit and validator results table.
Summarize a video by calling the VLM NIM or the Long Video Summarization (LVS) microservice directly. For short videos (under 60s) call the VLM's OpenAI-compatible chat completions endpoint; for long videos (60s or longer) call the LVS microservice. Use when asked to summarize a video, describe what happens in a video, analyze a recording, call or debug LVS summarize/model/health/recommended-config/metrics endpoints, or configure and troubleshoot the LVS service that backs long-video summarization.
Use skill if you are running many small Codex-native web searches through codex exec with per-question files and parseable answer artifacts.
Feishu Real-time Event Subscription (WebSocket). Use `event list` to view supported EventKeys; `event schema` to check event payload/scope; `event consume` to start long-connection subscription, where event streams are written to stdout in NDJSON format (blocking, one process subscribes to one EventKey); `event status` to view active local consume processes; `event stop` to terminate consume processes by PID / EventKey / --all. Supports over 22 EventKeys (including IM message receive/read/recall/reaction, group member changes, contact employee changes, calendar changes, cloud disk title/collaborator changes, approval instances and tasks, VC meeting start/end). Status files: ~/.feishu-cli/events/<app_id>/bus.json + flock file lock + WebSocket auto-reconnect. This skill is applicable when users request "listen to Feishu events", "real-time message event reception", "approval callback subscription", "event stream", "WebSocket long-connection listening", "event consume", "event list / schema / status / stop", "AI Agent bot real-time response". Note: This skill only handles subscription; for event webhook business logic (pushing to Feishu messages/writing to multidimensional tables), please use with feishu-cli-msg / feishu-cli-bitable.
Platform-neutral guidance for using Open Computer Use, the open-source Computer Use MCP server and CLI for macOS, Linux, and Windows. Use when an agent needs to install, verify, troubleshoot, configure, or operate Open Computer Use through its native CLI, stdio MCP server, or direct Computer Use tool calls.
DingTalk Workspace CLI (dws) — cross-platform tool for managing DingTalk enterprise data (contacts, calendars, docs, todos, AI tables, chat) via command line and AI agents
MCP server for real-time Three.js scene inspection, material editing, shader debugging, and performance monitoring from AI agents
Use when the user asks you to start, join, or continue a conversation with other agents via chatter, agent-chat, or talking to other agents about X.
This skill should be used when the user asks to "repair an agent", "audit an agent", "fix my agent", "review agent quality", "check if my agent is well-written", "diagnose agent problems", "what's wrong with this agent", "improve this agent", or "what's wrong with this agent file". Not for skills — use repair-skill.