codebase-auditor

Automate code reviews by running comprehensive codebase audits that detect security vulnerabilities aligned with OWASP Top 10, quality issues, and technical debt across JavaScript, TypeScript, and Python. The Skill analyzes your codebase in phases—Discovery, Deep Analysis, and Report—then generates prioritized remediation plans with severity levels and effort estimates to guide your team through fixes.

Yes, incremental audits support large codebases by analyzing portions of your codebase over time rather than requiring full scans each run. This reduces processing overhead while maintaining consistent quality assessment, allowing you to integrate audits into CI/CD pipelines and quality gates without performance impact.

Codebase audits generate prioritized remediation plans in multiple formats—Markdown, JSON, and HTML—so you can consume results in your preferred workflow. Each output includes severity levels (P0-P3), effort estimates, and actionable findings for security, quality, and technical debt issues.

Code auditing supports multi-language stacks including JavaScript, TypeScript, and Python, analyzing each for quality issues, security vulnerabilities, and SOLID principle adherence. The audit applies consistent 2024-25 SDLC standards and OWASP Top 10 alignment across all supported languages.

Code audits integrate with CI/CD pipelines to enforce quality gates by identifying blockers and tracking DORA metrics—deployment frequency, lead time, change failure rate, and recovery time. Automated scanning ensures standards compliance before release and provides data to measure delivery performance improvements.

Automated audits are consistent, standards-based, and detect issues—like OWASP Top 10 vulnerabilities and technical debt—that manual reviews often miss, while operating at scale across large codebases. Manual reviews remain valuable for design decisions, but audits remove time-consuming busywork and reduce human oversight gaps.