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Found 50 Skills
Use when the user wants to author, refine, or audit a Product Requirements Document for AI coding agents. Walks through an 8-phase pipeline (Socratic discovery → PRD draft → acceptance criteria → adversarial review → task decomposition → AI-readiness gate → test generation → handoff). Triggers on "write a PRD", "spec this feature", "draft requirements", "prepare X for Claude/Cursor/Copilot/Windsurf/Aider to build", "audit my PRD", "is this PRD AI-ready", "score this spec".
Create implementation task plans in `_/local-plans/<plan-name>.md`. First investigate the codebase using the Explore Agent, then document it in verifiable granularity and parallel-executable units, following the standard format (Background & Purpose, Current Status, Design, File Structure Tree, Implementation Steps, Verification Methods) that can be validated by the plan-verifier Agent. Used for requests like "Make a plan", "Design", "Task decomposition", "Think about implementation approach". plan, planning, design, implementation plan, task decomposition, create-plan
Shortcut alias for /superplan. Produce higher-quality code by breaking a feature into small, focused tasks the coding agent can nail one at a time. Works like an engineering team: feature → milestones → ~30-min tasks with specific files, acceptance criteria, and dependencies. Each task runs in a fresh context — narrow scope, full attention, one git commit per task.
Create a safe implementation plan as both markdown and JSON DAG artifacts. Challenge scope with the user first, explore real code before decomposing, then emit atomic TASK-NNN entries with explicit dependencies, write scope, validation, and assigned agents. Use when the user asks to plan, decompose, or break work into execution-ready tasks.
You MUST use this when an approved design or settled requirements need a detailed multi-step implementation plan before code changes begin.
Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, and LLM-as-a-judge verification
Convert one approved idea into an executable project when probe next routes project_setup.
Decompose the unified docs/specs/ artifact into parallelizable tasks — the ## Decomposition section of the same document whose ## Design & Rationale section holds the DR-N source. Triggers: 'plan implementation', 'create tasks from spec', or /plan. Applies the verification ladder: verification depth matches each task's blast radius — static analysis for low-risk tasks, scoped tests plus a kill-probe for medium, the integration suite on top for high-risk surfaces (judged test-after, not test-first ordering). Auto-chained from /ideate, or run directly to author the whole unified spec at thin/standard depth. Do NOT use for brainstorming, debugging, or code review.
This skill should be used when the user asks to "팀 구성해줘", "team assemble", "전문가 팀으로 해줘", "팀으로 해줘", "swarm", "병렬로 전문가 팀", or wants to decompose a complex task into specialist roles executed via TeamCreate. Also triggers when user describes a task clearly benefiting from parallel expert execution.
Default task orchestrator for all development and investigation work. Classifies tasks, decomposes into parallel workstreams if appropriate, and routes execution through the recipe runner. Replaces ultrathink-orchestrator.
Use when the contract is signed and work packages need to be created — decomposes the contract into bite-sized tasks, sets up git isolation, allocates territories and token budgets, producing the war plan
Decomposition playbook + anti-temptation rules for an orchestrator profile routing work through Kanban. The "don't do the work yourself" rule and the basic lifecycle are auto-injected into every kanban worker's system prompt; this skill is the deeper playbook when you're specifically playing the orchestrator role.