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Found 728 Skills
[Testing] Autonomous subagent variant of code-review. Use when reviewing code changes, pull requests, or performing refactoring analysis with focus on patterns, security, and performance.
Create subagent definitions for Claude Code and OpenCode that delegate to skills. Use when creating new subagents or refactoring existing ones to follow the delegation pattern.
Full-stack development skill with six-layer architecture, supporting cross-layer modifications initiated from any layer. It automatically coordinates the collaboration of six layers: UI Layer/Frontend Service Layer/Frontend API Layer/Backend API Layer/Backend Service Layer/Data Layer, enabling cross-layer consistent code generation and refactoring. Suitable for Vue3+FastAPI+PostgreSQL tech stack
Style, review, and refactoring standards for Python codebases with strong typing, explicit error handling, and maintainable module boundaries. Use when Python artifacts are created, changed, or reviewed and Python-specific quality rules must be enforced.
Bounded codebase exploration and architecture mapping. Use when discovery is needed before implementation. Do NOT use for broad refactoring — use do-plan instead.
Implement OpenAI Harness Engineering practices in any repository. Use when setting up or refactoring agent-first workflows, writing or upgrading AGENTS.md and PLANS.md, creating deterministic smoke/test/lint/typecheck harness commands, defining strict architecture boundaries and data-shape contracts, wiring observability from day 1, and adding entropy-control checks plus CI automation for reliable autonomous runs.
Use when working with code refactoring context restore
Apply DX-first heuristics to implementations, refactors, reviews, and debugging. Use when the user asks for code review, refactoring guidance, API design feedback, maintainability/readability improvements, or “make this easier to debug/onboard”.
Go-specific code review with 6-phase methodology: Context, Automated Checks, Quality Analysis, Specific Analysis, Line-by-Line, Documentation. Use when reviewing Go code, PRs, or auditing Go codebases for quality and best practices. Use for "review Go", "Go PR", "check Go code", "Go quality", "review .go". Do NOT use for writing new Go code, debugging Go bugs, or refactoring -- use golang-general-engineer, systematic-debugging, or systematic-refactoring for those tasks.
SOLID principles checklist with Java examples. Use when reviewing classes, refactoring code, or when user asks about Single Responsibility, Open/Closed, Liskov, Interface Segregation, or Dependency Inversion.
Analyzes codebases to identify refactoring opportunities based on Martin Fowler's catalog of code smells and refactoring techniques. Detects duplicated code, high coupling, complex conditionals, primitive obsession, long functions, and other structural issues. Produces a structured refactoring report with prioritized findings saved to docs/_refacs/. Use when auditing code quality, preparing for a refactoring sprint, or reviewing architectural health. Don't use for style/formatting issues, performance optimization, or security audits.
Guides systematic PyTorch recommender-system model development across compact data facts, existing source code, configs, focused tests, and training loops without overloading context from broad research archives. Use when building, debugging, or refactoring torch/nn.Module RecSys models with Transformer/HSTU/attention blocks, sparse/dense/list feature fusion, pCVR/CTR heads, ablation axes, or competition codebases where many model ideas exist but bugs and interface drift must be controlled. 用来指导推荐系统 PyTorch 模型开发、Transformer/HSTU 建模、关键数据事实、特征交互、shape/debug、训练闭环和已有模型结构的系统化推进。