Total 30,875 skills, Code Quality has 1629 skills
Showing 12 of 1629 skills
Iterative Five Whys root cause analysis drilling from symptoms to fundamentals
Generate nested AGENTS.md coding guidelines per module (monorepo-aware), detect languages/tooling, ask architecture preferences, and set up missing formatters/linters (Spotless for JVM). Use when the user wants module-scoped AGENTS.md coding guidelines or to set up missing formatters/linters.
Python development guidance with code quality standards, error handling, testing practices, and environment management. Use when writing, reviewing, or modifying Python code (.py files) or Jupyter notebooks (.ipynb files).
Use after implementing features - 7-criteria code review with MANDATORY artifact posting to GitHub issue; blocks PR creation until complete
Remove code comments via natural language guidance, suitable for simple scenarios in languages such as Python, JavaScript, TypeScript (.ts/.tsx), Java, C/C++, Go, HTML, etc.
Use before code review - determine if change is minor (review new code only) or major (review impacted code too)
Deep Python code review of changed files using git diff analysis. Focuses on production quality, security vulnerabilities, performance bottlenecks, architectural issues, and subtle bugs in code changes. Analyzes correctness, efficiency, scalability, and production readiness of modifications. Use for pull request reviews, commit reviews, security audits of changes, and pre-deployment validation. Supports Django, Flask, FastAPI, pandas, and ML frameworks.
Predicts future bug hotspots by analyzing code complexity, churn, and historical defect patterns. Warns developers before a bug is even written.
Executes large-scale architectural refactoring and technical debt reduction across the entire codebase. Ensures consistency with modern design patterns.
Manages the graceful decommissioning of underused or high-maintenance features. Plans deprecation cycles, handles data archiving, and generates migration paths for legacy users.
Architectural refactoring guide for Rust applications covering type safety, ownership patterns, error handling strategies, API design, project organization, module structure, naming conventions, conversion traits, and idiomatic patterns. Use when refactoring Rust codebases, reviewing PRs for architectural issues, improving type safety, designing error handling strategies, or organizing project structure. Complements the rust-optimise skill (performance patterns). Does NOT cover performance optimization, memory allocation, or async concurrency tuning (see rust-optimise skill).
Manages the structured relationship between ScriptableObjects (Data) and Prefabs (Logic/Visuals) in Unity 6. Follows the 'SO-to-Mono' Bridge pattern to ensure instance independence (e.g., individual health for identical robots) while maintaining a clean, data-driven architecture. Use when: (1) Creating new unit/item types, (2) Wiring SO data to Prefab MonoBehaviours, (3) Resolving data-sharing bugs where changing one SO affects all instances.