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Found 13,614 Skills
Use the `orca` CLI to drive a running Orca editor — manage Orca worktrees; create, read, and run shell commands in Orca-managed terminals; and automate Orca's built-in browser (snapshot/click/fill/screenshot/tabs). Use this instead of raw `git worktree`, ad hoc shell PTYs, or Playwright whenever the task touches Orca state. Coding agents inside an Orca worktree should also use it to keep the worktree comment fresh at meaningful checkpoints. Boundary with `orchestration`: if the recipient of a terminal write is another AI agent (Claude Code, Gemini, Codex, a worker), use `orchestration` — it is the only correct way to send messages, nudges, replies, or task hand-offs to agents. orca-cli writes are for non-agent terminals (shells, build/test commands); reading or `wait`ing on any terminal — including agent terminals — stays in orca-cli.
Compounding knowledge across projects and teams. Captures, searches, and promotes institutional learnings via tiered backends (local/qmd/agent-fs).
Design and build LLM-powered projects from ideation through deployment. Use when starting new agent projects, choosing between LLM and traditional approaches, or structuring batch processing pipelines.
Design and implement memory architectures for agent systems. Use when building agents that need to persist state across sessions, maintain entity consistency, or reason over structured knowledge.
Create and run durable workflows with steps, streaming, and agent execution. Covers starting, resuming, and persisting workflow results.
Sanitize OpenClaw agent output before display. Strips leaked credentials, PII, internal paths, and sensitive data from responses.
Marketing skills for AI agents. CRO, copywriting, SEO, analytics, pricing, and growth engineering. From Corey Haines' Marketing Skills collection. Use when working with marketing, cro, conversion, copywriting, seo, landing page, pricing, growth.
Build features guided by data insights, A/B testing, and continuous measurement using specialized agents for analysis, implementation, and experimentation.
Automatic agent selection and intelligent task routing. Analyzes user requests and automatically selects the best specialist agent(s) without requiring explicit user mentions.
Guide for creating effective skills. Use when you want to create a new skill (or update an existing skill) that extends an agent with specialized workflows, tool integrations, or repo conventions.
After the task execution is completed, prompt the user to open a new Agent to review the uncommitted git code. Athletes should not act as referees; proceed with the wrap-up only after the review is approved.
Expert prompt engineering for LLM applications including prompt design, optimization, RAG systems, agent architectures, and AI product development.