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Found 41 Skills
AI 에이전트와 협업하는 에이전틱 개발의 범용 원칙. 분해정복, 컨텍스트 관리, 추상화 수준 선택, 자동화 철학을 정의. 모든 AI 코딩 도구에 적용 가능.
The ultimate autonomous dev pipeline. Combines wavybaby (CoVe verification, skill discovery, MCP tooling) + GSD (roadmaps, phases, plans, discovery, state tracking) + Ralph (autonomous loop with circuit breakers). Generates a PRD, equips itself with the best tools, bootstraps a full GSD .planning/ structure, then runs Ralph to autonomously execute each plan with CoVe-verified code until the milestone is complete.
A comprehensive verification system for Claude Code sessions.
CRITICAL: Use for agent-spec CLI tool workflow. Triggers on: agent-spec, contract, lifecycle, guard, verify, explain, stamp, checkpoint, spec verification, task contract, spec quality, lint spec, run log, "how to verify", "how to use agent-spec", "spec failed", "guard failed", contract review, contract acceptance, PR review, code review workflow, 合约, 验证, 生命周期, 守卫, 规格检查, 质量门禁, 合约审查, "验证失败", "怎么用 agent-spec", "spec 不通过", "工作流"
Run the sefirot loop and confirm with the user if there are any questions
Use this skill for mathematical code verification. Use when reviewing math-heavy code, verifying algorithm correctness, checking numerical stability, aligning with mathematical standards. Do not use when general algorithm review - use architecture-review. DO NOT use when: performance optimization - use parseltongue:python-performance.
Use when you want to validate changes before committing, or when you need to check all React contribution requirements.
Load automatically when user asks to learn Medusa development (e.g., "teach me how to build with medusa", "guide me through medusa", "I want to learn medusa"). Interactive guided tutorial where Claude acts as a coding bootcamp instructor, teaching step-by-step with checkpoints and verification.
Run verification commands and confirm output before claiming success. Use when about to claim work is complete, fixed, or passing, before committing or creating PRs.
Code review practices with technical rigor and verification gates. Use for receiving feedback, requesting code-reviewer subagent reviews, or preventing false completion claims in pull requests.
Synthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than any single model.
Build AdonisJS 6 features from scratch through production. Full lifecycle - build, debug, test, optimize, refactor. Follows TypeScript-first, Lucid ORM, and AdonisJS conventions.