Ruff Linting

What it does

This skill enables AI agents to perform static code analysis on Python projects using Ruff, a fast and reliable linter. It identifies syntax errors, style issues, and potential bugs to ensure code quality and consistency across your codebase.

When to use it

• Before committing changes to enforce strict coding standards and prevent regressions.
• During code reviews to automatically flag common mistakes like unused variables or incorrect imports.
• When refactoring legacy codebases to modernize syntax and improve readability.
• In CI/CD pipelines to block deployments that fail linting checks.

Key capabilities

• Fast execution: Leverages Rust for near-instant analysis of large Python files.
• Comprehensive rule sets: Supports hundreds of rules covering pycodestyle, pyflakes, and isort.
• Fixable issues: Automatically corrects many common errors without manual intervention.
• Configurable rules: Allows customization via configuration files to tailor strictness levels.

Example prompts

• "Run a full linting check on my Python project and list all critical errors."
• "Fix any style violations in the src/utils.py file using Ruff's auto-fix feature."
• "Analyze this code snippet for security vulnerabilities and formatting issues."

Tips & gotchas

Ensure your project has a pyproject.toml or .ruff.toml configuration file to define custom rules if needed. Some complex logic errors may require manual review even after linting passes.