Browse 3000+ community-built OpenClaw skills organized by capability layers, real-world use cases, download popularity, and security readiness.
OpenClaw Skills helps developers discover, compare, and choose the best OpenClaw skills for AI agents — faster, safer, and with less trial-and-error.
Data Source: ClawHub & Community Metrics · Updated: Monthly
Hand-picked high-impact OpenClaw skills based on download volume, stability, and real-world usage.
OpenClaw skills are structured into four capability layers to help developers build stable AI agent systems from foundation to guardrails.
Browser automation, API integration, DevOps control, workflow execution. Representative Skills: agent-browser · playwright · docker · kubernetes · github
Web search, research agents, structured extraction, multi-source querying. Representative Skills: tavily · perplexity · exa · deep-research · searxng
Persistent context, task planning, structured document management. Representative Skills: triple-memory · planning-with-files · file-search
Prompt injection mitigation, policy enforcement, risk detection. Representative Skills: security-sentinel · zero-trust · safe-exec
OpenClaw skills provide modular capability units that extend AI agents with real-world functionality.
Skills are designed for real-world deployment with proper error handling, logging, and reliability built in.
Security-focused skills help validate inputs and protect your agents from malicious prompts.
Memory skills provide short-term, working, and long-term context persistence for stateful agents.
Foundation layer skills enable web automation, container management, and CI/CD integration.
Intelligence layer skills connect your agents to web search, research tools, and external APIs.
The Capability Pyramid helps you structure agent capabilities from execution to security guardrails.
Common questions about OpenClaw skills and this directory.