Discover blockchain code quality skills, compare source repositories and read the instructions for each workflow.
The model must use this skill when : 1. working within any python project. 2. Python CLI applications with Typer and Rich are mentioned by the user. 2. tasked with Python script writing or editing. 3. building...
The model must invoke this skill when any trigger occurs - (1) user mentions "clang-format" or ".clang-format", (2) user requests analyzing code style/formatting patterns/conventions, (3) user requests creating...
When setting up automated code quality checks on git commit. When project has .pre-commit-config.yaml. When implementing git hooks for formatting, linting, or validation. When creating prepare-commit-msg hooks...
This skill should be used when the model needs to ensure code quality through comprehensive linting and formatting. It provides automatic linting workflows for orchestrators (format → lint → resolve via concurr...
When setting up commit message validation for a project. When project has commitlint.config.js or .commitlintrc files. When configuring CI/CD to enforce commit format. When extracting commit rules for LLM promp...
Review code for quality, bugs, security, and improvements. Use when self-reviewing before commit, reviewing PRs, or debugging issues.
Run comprehensive CI checks before committing changes. Use when the user asks to run CI, run quality checks, validate code quality, or before finishing any task that involves code changes.
Enforce code organization principles - "Directory X contains ONLY class type X", DDD naming patterns, PHP best practices, type safety, and SOLID principles. Use when reviewing code structure, placing classes, o...
Maintain and improve code quality using PHPInsights without decreasing quality thresholds. Use when PHPInsights fails, cyclomatic complexity is too high, code quality drops, or when refactoring for better maint...
Systematically retrieve and address PR code review comments using make pr-comments. Use when handling code review feedback or addressing PR comments.
Use when user asks to "analyze codebase", "scan project", "detect tech stack", or mentions "codebase analysis", "existing code", "collision risk", "brownfield", or "project context".
Use when asked to find code smells, audit TODOs, remove dead code, clean up unused imports, delete debug statements, or assess code quality. Triggers on: "use tech-debt mode", "tech debt", "code smells", "clean...
Scan for security vulnerabilities in dependencies, code patterns, and secrets. Uses project-documented tooling where available.
Multi-agent code verification workflow using a main agent and sub-agent loop. Use when verifying code against requirements, acceptance criteria, or quality standards. Triggers on requests to verify, validate, o...
Detect technical debt patterns in code including duplication, complexity, and maintainability issues. Use at phase checkpoints or on-demand to assess code quality.
Run code quality linters when reviewing code. Checks style, complexity, and best practices. Supports Python (ruff), JavaScript (eslint), Go (golangci-lint), Ruby (rubocop), Java (Checkstyle/PMD). Use when revie...
Generate comprehensive test coverage reports when reviewing code. Identifies untested code paths and low-coverage areas. Supports Python (pytest-cov), JavaScript (jest), Go (go test -cover), Java (JaCoCo). Use...
Run comprehensive security vulnerability scans when reviewing code. Automatically uses basic mode (fast, high/medium severity only) for first reviews, advanced mode (comprehensive, all severities) for iteration...
Formats and prettifies JSON with configurable indentation
AI-powered code review tool that analyzes code for bugs, style issues, and improvements
Formats and prettifies JSON with configurable indentation
Performance profiling and optimization. Use for benchmarking code, analyzing performance, running Lighthouse audits, and finding hotspots.
Code refactoring with AI assistance. Use for modernizing code, converting JavaScript to TypeScript, class to hooks conversions, and systematic renaming.
Generate tests using AI and run test suites. Use for generating unit tests, running coverage reports, and mutation testing.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.