codebase-audit

A codebase audit identifies quality issues by running a 14-check cascade across Python and TypeScript projects to detect dead code, duplication, dependency risks, and architectural anti-patterns. Findings are aggregated into a structured health score for prioritized remediation.

You can audit Python and TypeScript projects by running a cross-language cascade workflow that checks architecture, dead code, dependencies, and security. The process uses detailed reference checklists for backend and frontend patterns to identify anti-patterns and calculate a health score.

Yes, automated codebase reporting can be applied during CI checks or full risk assessments. The audit enforces a cascade workflow to evaluate code quality and exports a ready-to-use standardized report with thresholds to guide fixes.

Yes, this codebase audit supports cross-language audits covering both Python and TypeScript. It provides detailed reference checklists tailored for backend and frontend patterns to ensure comprehensive quality and risk analysis across your stack.

The best way to prioritize fixes is by using the structured health score generated from the audit cascade. The standardized report provides thresholds and guidance to rank dead code, duplication, and dependency issues based on their impact on overall codebase health.

The cascade workflow is designed specifically for Python and TypeScript projects, meaning it may not support other programming languages. Additionally, the audit relies on predefined thresholds and reference checklists to evaluate risks, which might require manual tuning for unique architectural contexts.