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Found 534 Skills
Integrate Honcho memory and social cognition into existing Python or TypeScript codebases. Use when adding Honcho SDK, setting up peers, configuring sessions, or implementing the dialectic chat endpoint for AI agents.
Amazon Bedrock AgentCore Evaluations for testing and monitoring AI agent quality. 13 built-in evaluators plus custom LLM-as-Judge patterns. Use when testing agents, monitoring production quality, setting up alerts, or validating agent behavior.
Add email capabilities to AI agents using popular frameworks. Provides pre-built tools for TypeScript and Python frameworks including Vercel AI SDK, LangChain, Clawdbot, OpenAI Agents SDK, and LiveKit Agents. Use when integrating AgentMail with agent frameworks that need email send/receive tools.
This skill enriches vague prompts with targeted research and clarification before execution. Should be used when a prompt is determined to be vague and requires systematic research, question generation, and execution guidance.
Audits agent skill instructions and system prompts for vulnerabilities to prompt hijacking and indirect injection. Use when designing new agent skills or before deploying agents to public environments where users provide untrusted input.
Claude Code Agent Teams - default team-based development with strict TDD pipeline enforcement
Use when starting any conversation - establishes mandatory workflows for finding and using skills, including using Skill tool before announcing usage, following brainstorming before coding, and creating TodoWrite todos for checklists
Facilitate workshop sessions in a multi-turn, one-step flow with numbered recommendations at decision points and quick-select options for regular questions.
A 'skill for creating skills'. This tool automates the entire process of converting any GitHub repository into a standardized Trae skill, and is a core tool for expanding AI Agent capabilities.
Hybrid memory strategy combining OpenClaw's built-in QMD vector memory with Graphiti temporal knowledge graph. Use for all memory recall requests.
After an agentic task completes, perform a retrospective analysis across 6 dimensions (goal alignment, efficiency, decision quality, error handling, communication, reusability). Score performance, identify inefficiency patterns, evaluate skill usage, and produce actionable improvement recommendations. Triggers on "how did it go", "retrospective", "review performance", "what could be better", or after any long agentic task completes.
Create and configure Claude Code sub-agents with custom prompts, tools, and models