Loading...
Loading...
Found 31 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.
Use when starting a session, deciding which framework skill applies to the current task, or sequencing them across a feature. Maps the user's intent to one of the five framework skills (ai-driven-prd, init-claude-project, generate-dev-plan, declarative-design, execute-plan) and enforces the cross-skill operating behaviors. Triggers on "which skill should I use", "where do I start", "how do these skills fit together", "I have a PRD now what", "/using-agent-skills".
Generate and use a pre-edit structure brief so coding agents learn likely owners, consumer surfaces, and unsafe edit locations before implementing.
Use when executing multi-task plans where each task can be implemented independently by a subagent. Triggers when a plan has 3+ independent tasks, when speed of execution is important, when tasks have clear acceptance criteria suitable for delegation, or when two-stage review gates (spec compliance and code quality) are needed for iterative fix cycles.
Retrieve the latest Runway API reference from docs.dev.runwayml.com and use it as the authoritative source before any integration work
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.
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.
Capture AI agent sessions in your git workflow. Use for setup, rewinding to checkpoints, exploring session history, and troubleshooting.
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.
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.