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Found 23 Skills
AI 에이전트 협업 개발의 핵심 원칙. 분해정복, 컨텍스트 관리, 추상화 수준 선택, 자동화 철학, 검증 회고를 정의. 모든 AI 에이전트 사용 시 최적의 협업 패턴 적용.
Use this skill when working with Conductor's context-driven development methodology, managing project context artifacts, or understanding the relationship between product.md, tech-stack.md, and workflow.md files.
Retrieve the latest Runway API reference from docs.dev.runwayml.com and use it as the authoritative source before any integration work
Claude Code Advanced Development Guide - A comprehensive tutorial covering tool usage, REPL environment, development workflows, MCP integration, advanced patterns, and best practices. Ideal for learning Claude Code's advanced features and development techniques.
OpenAI integration. Manage Assistants, Files. Use when the user wants to interact with OpenAI data.
Use when the workflow works but needs polish, or as the final step in a diagnose → fix → refine cycle before shipping.
Curated documentation reference for developers building with Pinecone. Contains links to official docs organized by topic and data format references. Use when writing Pinecone code, looking up API parameters, or needing the correct format for vectors or records.
Look up Gemini API documentation, SDK patterns, and current best practices when building with Google Gemini. Maps topics to local cached docs and live sources, provides correct @google/genai patterns, and highlights deprecated vs current API usage. Trigger with 'gemini docs', 'gemini guide', 'how to use gemini', 'gemini SDK', '@google/genai', or when building code that imports from @google/genai or google-genai.
Integrated AI agent orchestration skill that combines plannotator, ralphmode, team or bmad execution, agent-browser verification, and agentation feedback loops, while maintaining a project-local `.jeo` ledger for planning, development, and QA. Use when the user wants an end-to-end multi-agent workflow with plan approval, implementation, UI review, cleanup, and durable task history. Triggers on: jeo, annotate, ui-review, multi-agent orchestration.
Fix broken AI features. Use when your AI is throwing errors, producing wrong outputs, crashing, returning garbage, not responding, or behaving unexpectedly. Covers DSPy debugging, error diagnosis, and troubleshooting.
Ollama API Documentation
Use when the user asks to "plan this feature", "plan refactor", "research & plan", "plan auth/API/work", or needs multi-step work with evidence-based planning before coding. Understands → Researches (via Local Search/Research) → Plans → Implement. No guessing; validates with code.