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Found 811 Skills
Systematic codebase quality scan for identifying duplication, redundancy, and improvement opportunities. Use when reviewing a repo's architecture, finding refactoring targets, or assessing code health. Triggers: "scan the repo", "find code duplication", "suggest improvements", "code quality review", "is there redundant code", "refactoring plan", "architecture review".
General Correctness rules, Rust patterns, comments, avoiding over-engineering. When writing code always take these into account
Write-time code quality enforcement using Plankton — auto-formatting, linting, and Claude-powered fixes on every file edit via hooks.
Code quality improvement: review, refactoring, debugging. Phases: review feedback, systematic refactoring, root cause debugging, verification. Capabilities: SOLID/DRY compliance, code smell detection, complexity reduction, bug investigation, verification gates. Actions: review, refactor, debug, verify, validate code. Keywords: code review, refactor, debug, SOLID, DRY, code smell, bug fix, root cause, verification, technical debt, extract method, test failure, completion claim. Use when: reviewing code changes, improving code quality, fixing bugs, reducing technical debt, validating before merge/commit.
Code quality audit worker (L3). Checks cyclomatic complexity, deep nesting, long methods, god classes, method signature quality, O(n²) algorithms, N+1 queries, magic numbers/constants. Returns findings with severity, location, effort, recommendations.
Comprehensive quality gate integrating linting, type checking, specification review, and security auditing.
Clean code principles, SOLID, and code review practices
Python code quality with ruff (linting & formatting) and mypy (type checking). Covers pyproject.toml configuration, pre-commit hooks, and type hints. Use when user mentions ruff, mypy, linting, formatting, type checking, code style, or Python code quality.
Run code quality checks (ruff, mypy, pytest) and optionally simplify code. This skill should be used when the user wants to check code quality, run linters, run tests, or simplify recently modified code. Triggered by /lint, /check, or /code-quality commands.
Provides guidance on fundamental software design principles to reduce complexity, prevent over-engineering, and improve maintainability.
Worker that checks DRY/KISS/YAGNI/architecture compliance with quantitative Code Quality Score. Validates architectural decisions via MCP Ref: (1) Optimality (2) Compliance (3) Performance. Reports issues with SEC-, PERF-, MNT-, ARCH-, BP-, OPT- prefixes.
Provides general code quality and best practices guidance applicable across languages and frameworks. Focuses on linting, testing, and type safety.