Code Health
Use when the user asks about code health, code quality, complexity, technical debt...
Install
npx skills add repowise-dev/repowise --skill code-health -g -a claude-code -y- Repository
- repowise-dev/repowise8.1k
- Category
- Engineering
- Updated
- 3d ago
- License
- AGPL-3.0
- Context cost
- Lightabout 716 tokens
- Runs scripts
- No, instructions only
What it does
Use when the user asks about code health, code quality, complexity, technical debt, which files are risky or hard to maintain, what to refactor next, untested hotspots, or coverage gaps in a Repowise-indexed codebase (.repowise/ directory exists). Also use to get a before/after health read when planning or finishing a refactor.
Code Health with Repowise
Repowise scores every file 1, 10 from deterministic markers, McCabe complexity, deep nesting, brain methods, class cohesion (LCOM4), god classes, clone detection, untested hotspots, function-level churn, ownership dispersion, and more. Zero LLM calls; pure local analysis. The weights are calibrated against a real defect corpus, so a low score means more likely to harbour bugs, not just bigger.
Pick the mode by what you pass
- Dashboard:
get_health()(no targets):fix_first, the ranked list of what to fix first, then repo-level KPIs and the lowest-scoring files. Start here for "how healthy is this codebase?" or "what should we clean up?". - Targeted,
get_health(targets=["src/x.py", "src/y.py"]): per-file score and the specific marker findings driving it. Use before/after a refactor, or to explain why a file is flagged.
Useful include flags
get_health(targets=[...], include=[...]):
"biomarkers", always return the findings list (what's wrong, where)."refactoring", deterministic, ranked refactoring suggestions (by impact/effort)."coverage", surface coverage data when it's been ingested."trend", recent health snapshots + declining / predicted-decline signal.
include adds blocks; only=[...] subtracts them.
