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Found 1,689 Skills
Self-writing meta-extension that forges new capabilities — researches docs, writes extensions, tools, hooks, and skills
Create, list, remove, and run scheduled autonomous Claude Code agents. Agents run on a timer via macOS launchd, execute any prompt headlessly, and deliver results via Beeper messages and macOS notifications. Use for recurring research, monitoring, overnight builds, or any task you want Claude to do on autopilot.
Day 2 보충 자료 - MCP 딥다이브. Claude Code에 외부 도구를 연결하는 MCP를 체계적으로 배운다. "MCP 배우기", "MCP 보충", "MCP 강의", "MCP 학습" 요청에 사용.
Build AI applications using Azure AI Projects SDK for JavaScript (@azure/ai-projects). Use when working with Foundry project clients, agents, connections, deployments, datasets, indexes, evaluations, or getting OpenAI clients.
Orchestrate multiple Antigravity skills through guided workflows for SaaS MVP delivery, security audits, AI agent builds, and browser QA.
AI's Knowledge Base CLI - Query and manage world knowledge for AI agents. Use when users want to search knowledge, add knowledge sources, or interact with the worldbook knowledge base. This is a CLI-first approach that treats AI agents as first-class citizens.
Guide on using oh-my-claudecode plugin
Create a new implementation plan file for new features, refactoring existing code or upgrading packages, design, architecture or infrastructure.
Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. This skill covers the Interactions API, the recommended way to use Gemini models and agents in Python and TypeScript.
Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.
Engineering operating model for teams where AI agents generate a large share of implementation output.