Total 44,010 skills, Code Quality has 2062 skills
Showing 12 of 2062 skills
Holistic, system-aware planning before implementing non-trivial tasks. Use when the task involves new features, architectural decisions, multi-file changes, unclear requirements, or multiple valid approaches. Triggers on "/plan", "plan this", "design an approach", "let's plan first".
Auto-extract patterns from coding sessions, track corrections, and build reusable knowledge with confidence scoring
Semgrep integration. Manage Rules, Scans. Use when the user wants to interact with Semgrep data.
This skill embodies the principles of "Clean Code" by Robert C. Martin (Uncle Bob). Use it to transform "code that works" into "code that is clean."
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
Use this skill when > Request a broader architectural perspective when navigating unfamiliar code sections. Maps all relevant modules, identifies caller relationships and dependencies, and uses domain-specific vocabulary. Use when encountering unfamiliar code or needing to understand how a component integrates with the larger system.
Use this skill when > Migrate TypeScript test files from unsafe `as` type assertions to type-safe alternatives from @total-typescript/shoehorn. Replace `obj as Type` with fromPartial(), `obj as unknown as Type` with fromAny(), and complete specs with fromExact(). Test code only — never use in production.
Architecture analysis, violation detection, and pattern validation. USE WHEN: reviewing code architecture, identifying violations, verifying patterns, updating technical documentation. Reference: docs/02-architecture/ARCHITECTURE.md Examples: <example> Context: User wants to check if code follows architecture. user: "Analyze if the payment module follows our architecture" assistant: "I'll use architecture-analyzer to review against ARCHITECTURE.md." <commentary>Architectural review is architecture-analyzer specialty.</commentary> </example> <example> Context: Need to identify technical debt. user: "Find architectural violations in the services layer" assistant: "I'll use architecture-analyzer to scan for violations." <commentary>Violation detection is architecture-analyzer responsibility.</commentary> </example>
Analyzes Java code against industry best practices and evaluates design principles including SOLID, exception handling, thread safety, and resource management. Reviews naming conventions, Stream API usage, Optional patterns, and general code quality. Use when reviewing Java files, checking code quality, evaluating exception handling, or auditing resource management.
Systematic resolution of pyright/mypy type errors with categorization and fix templates. Use when pyright fails, type errors are reported, adding type annotations, or enforcing type safety. Analyzes Python type errors, categorizes them (missing annotations, incorrect types, generic issues, Optional/None handling), and applies fix patterns. Works with .py files and pyright output.
Verifies that implemented code is actually integrated into the system and executes at runtime, preventing "done but not integrated" failures. Use when marking features complete, before moving ADRs to completed status, after implementing new modules/nodes/services, or when claiming "feature works". Triggers on "verify implementation", "is this integrated", "check if code is wired", "prove it runs", or before declaring work complete. Works with Python modules, LangGraph nodes, CLI commands, API endpoints, and service classes. Enforces Creation-Connection-Verification (CCV) principle.
Enforces the discipline of thinking about tests, features, and maintainability BEFORE writing implementation code. Use when starting new classes/methods, refactoring existing code, or when asked to "think about tests first", "design for testability", "what tests do I need", "test-first approach", or "TDD thinking". Promotes simple, maintainable designs by considering testability upfront. Works with any codebase requiring test coverage and quality standards.