reviewer

Code review automation uses metrics across complexity, security, maintainability, test coverage, and performance to score Python projects objectively. This Skill integrates Ruff, mypy, Bandit, jscpd, and pip-audit to detect issues fast and deliver actionable feedback with code examples for quality gates.

Yes, parallel execution of Ruff, mypy, Bandit, and pip-audit combines linting, type checking, security scanning, and dependency auditing in a single review. This Skill coordinates these tools to identify security vulnerabilities, code quality issues, and outdated packages simultaneously.

Duplication detection with jscpd combined with security scanning via Bandit and dependency auditing through pip-audit provides comprehensive coverage. This Skill structures findings with Context7 library documentation lookups to verify secure usage patterns.

Security scanning integrates with complexity, maintainability, and performance metrics through unified scoring and structured outputs. This Skill leverages Bandit for vulnerability detection, mypy for type safety, and contextual feedback to satisfy both human review and RAG pipeline requirements.

Yes, static analysis output becomes actionable through concrete recommendations and code examples tied to specific issues. This Skill transforms tool findings into structured data suitable for developers to remediate problems and systems to process programmatically.

Automated scoring quantifies measurable dimensions—complexity, security, maintainability, coverage, and performance—but requires human judgment on architectural tradeoffs and business logic. This Skill excels at flag-raising and trend detection; final decisions rest with code reviewers.