health-audit

An ecosystem health audit assesses technical debt across multiple repositories by calculating scores based on test coverage, code quality, dead code, and TODOs, identifying risk zones and providing prioritized recommendations.

Ecosystem health scoring evaluates a codebase by generating overall and per-repository scores derived from test coverage, code quality metrics, dead code ratios, and TODO burden to highlight specific areas needing remediation.

Identify risk zones before a refactor by running a health audit that flags areas with low scores, high dead code ratios, compilation errors, contract mismatches, and convention divergence across your repositories.

Yes, you can perform a deep dive into individual repository health during an ecosystem audit by dispatching a dedicated repo-analyst agent to investigate specific low-scoring areas and compilation issues.

Yes, the health audit detects ecosystem-level concerns by flagging convention divergence and contract mismatches between repositories, alongside calculating individual repository scores for test coverage and dead code.

Automated codebase analysis for risk assessment is limited to quantifiable metrics like test coverage, dead code, and TODOs, meaning it may not capture subjective architectural flaws or nuanced business logic risks without manual review.