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Found 1,204 Skills
Use when a managed library is ready to publish to GitHub and hand to teammates as an install command. Run the GitHub publishing steps, then return the exact shareable install command.
Use when the user wants to update, refresh, or reinstall the CopilotKit agent SKILLS (the SKILL.md files that teach this agent about CopilotKit). NOT for updating the CopilotKit codebase or project — this is specifically about refreshing the skills/knowledge this agent has loaded. Triggers on "update copilotkit skills", "update skills", "refresh skills", "skills are stale", "skills are outdated", "get latest skills", "my copilotkit knowledge is wrong", "copilotkit APIs changed", "skills seem old", "wrong API names", "reinstall skills", "skills not working right", "update your copilotkit knowledge".
This skill should be used when the user wants to "login to GitHub", "store an API key", "get authentication headers", "export credentials to the shell", "run a command with API keys injected", "register a custom OAuth provider", "manage tool tokens", or "authenticate to a third-party application". Also triggers for requests involving authenticating AI agents or securely storing/retrieving credentials using the authsome CLI.
Summarize the last N agent sessions for the current project, grouped by date. Use when the user asks "recap", "what have we been doing", "this week", "today", or wants a rollup of recent work.
The house format and rules for writing or updating an agentmemory skill. Use when adding a new skill, restructuring an existing one, or reviewing a skill contribution for consistency.
原始人スタイル subagent への委譲判断ガイド。`genshijin-investigator` (コード位置特定)、 `genshijin-builder` (1-2ファイル編集)、`genshijin-reviewer` (diff レビュー) を inline作業 or vanilla `Explore` の代わりにスポーンするタイミングを示す。subagent 出力は原始人圧縮 → 主コンテキストに戻る tool-result が約60%縮小 → 長セッション持続。 Trigger: 「subagent 委譲」「genshijin-crew 使用」「investigator/builder/reviewer 起動」「コンテキスト節約」「圧縮 agent 出力」。
Guides architectural decisions for Deep Agents applications. Use when deciding between Deep Agents vs alternatives, choosing backend strategies, designing subagent systems, or selecting middleware approaches.
LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications
Access paid services (verification, search, AI models, images, audio, browser automation) for AI agents via Sapiom. Use when building agents that need to verify phone/email, search the web, call AI models, generate images, convert text-to-speech, or automate browsers — without setting up vendor accounts.
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.
Transform extracted engineer expertise into an actionable skill with progressive disclosure, allowing agents to find and apply relevant patterns for specific tasks.
Automatically sync Agents.md, claude.md and gemini.md files in the project to maintain content consistency. Supports automatic monitoring and manual triggering.