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Found 460 Skills
Explore a codebase for architectural friction, discover refactoring opportunities, and propose module-deepening refactors as GitHub issue RFCs. Uses friction-driven exploration and parallel sub-agents to design multiple interface alternatives. Use when user wants to improve architecture, find refactoring opportunities, consolidate coupled modules, reduce complexity, make code more testable, or review codebase health.
Use when accepted findings require bounded repair changes and a structured repair summary.
Auto-activates when working with implementation plans. Triggers on "continue the plan", "next task", "what's the plan status", "run task 2.1", or when user references plans/*.plan.md files. Not for creating plans - use /superplan command for that.
3-에이전트(Architect→Builder→Reviewer) 루프로 단일 기능을 설계·구현·검증하는 팀 스킬. "3a로 만들어줘", "3에이전트", "설계-구현-검토", "team-3a" 키워드로 트리거. peach-team보다 가벼운 단일 기능·소규모 수정에 적합.
Ecosystem self-evolution orchestrator. Detects project lifecycle phases, evaluates agent relevance, synthesizes cross-agent knowledge, and proposes evolution actions (health checks, fitness scoring, evolution proposals).
Evaluate solutions through multi-round debate between independent judges until consensus
You are an **Agentic Identity & Trust Architect**, the specialist who builds the identity and verification infrastructure that lets autonomous agents operate safely in high-stakes environments. You...
LangGraph supervisor-worker pattern. Use when building central coordinator agents that route to specialized workers, implementing round-robin or priority-based agent dispatch.
This skill should be used when users request comprehensive, in-depth research on a topic that requires detailed analysis similar to an academic journal or whitepaper. The skill conducts multi-phase research using web search and content analysis, employing high parallelism with multiple subagents, and produces a detailed markdown report with citations.
Guide for decomposing large tasks into executable steps, managing dependencies and priorities, and distributing work across agents. Includes TodoList integration patterns.
Deep web research with parallel investigators, multi-wave exploration, and structured synthesis. Spawns multiple web-researcher agents to explore different facets of a topic simultaneously, launches additional waves when gaps are identified, then synthesizes findings. Use when asked to research, investigate, compare options, find best practices, or gather comprehensive information from the web.\n\nThoroughness: quick for factual lookups | medium for focused topics | thorough for comparisons/evaluations (waves continue while critical gaps remain) | very-thorough for comprehensive research (waves continue until satisficed). Auto-selects if not specified.
Orchestrate in-session Task tool teams for parallel work. Fan-out research, implementation, review, and documentation across subagents. Use when: parallel tasks, fan-out, subagent team, Task tool, in-session agents.