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Found 13,625 Skills
Generate structured prd.json files for autonomous agent loops (Ralph Wiggum pattern). Use when planning bulk/batch tasks, migrations, refactoring campaigns, or any work that can be decomposed into independent items with verification steps.
Interactive backlog grooming. Explore, brainstorm, discuss, then synthesize. Orchestrates agents and issue-creator skills. Creates prioritized GitHub issues. Enforces Misty Step org-wide standards.
Comprehensive code review with parallel specialist sub-agents. Analyzes requirements traceability, code quality, security, performance, accessibility, test coverage, and technical debt. Produces detailed findings and calls /qa-gate for final gate decision.
Break down complex tasks into atomic, actionable goals with clear dependencies and success criteria. Use this skill when you need to plan multi-step projects, coordinate agents, or decompose complex user requests into manageable sub-tasks.
Three-lens code review using parallel subagents: Epimetheus (hindsight — bugs, debt, fragility), Metis (craft — clarity, idiom, fit-for-purpose), Prometheus (foresight — vision, extensibility, future-Claude). Triggers on /titans, /review, 'review this code', 'what did I miss', 'before I ship this'. Use after completing substantial work, before /close. (user)
Compress documentation, prompts, and context into minimal tokens for AGENTS.md and CLAUDE.md. Achieves 80%+ token reduction while preserving agent accuracy.
TDD workflow for migrations - orchestrate agents, zero main context growth
Create new agent skills with best-practice templates. Guides through skill level selection (L0 pure prompt, L0+ with helper scripts, L1 with business scripts), environment strategy (stdlib/uv/venv), and generates ready-to-edit project files following runtime UX best practices. This skill should be used when creating a new skill, scaffolding a skill project, initializing skill templates, or when the user says 'help me build a skill', 'create a skill', '创建技能', '新建 skill'.
주식/ETF 분석 에이전트 공통 규칙. 웹검색 직접 호출, 원문 인용, 교차 검증 프로토콜을 정의합니다. 환각 방지의 핵심 방어선.
Interactive tutorial that guides engineers through building their own coding agent (agentic loop) from scratch using raw HTTP calls to an LLM API. Supports Gemini, OpenAI (and compatible endpoints), and Anthropic. Supports TypeScript, Python, Go, and Ruby. Detects progress automatically. Use when someone says "build an agent", "teach me agents", or "/build-agent".
Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM w...
Control interactive terminal sessions via tmux. Use when tasks need persistent REPLs, parallel CLI agents, or any process requiring a TTY that simple shell execution cannot handle.