Repowise · Codebase intelligence
nehant14 / repowise
Codebase intelligence for AI and humans: code health scores, auto-generated docs, git analytics, dead code detection, and architectural decisions via MCP.
Does the health score find the bugs?
Repowise ranks every file by predicted defect risk. Of the 20 files it flags as riskiest, 17 (85%) actually needed a bug fix in the last 6 months — 3.3× better than picking files at random.
Languages
- python59.1%
- typescript33.4%
- markdown3.7%
- json3.0%
- yaml0.3%
- toml0.2%
- shell0.1%
Key modules8
- typescript
api-client
packages/api-client
- python
cli
packages/cli
- python
core
packages/core
- python
server
packages/server
types
packages/types
How nehant14/repowise works
Codebase intelligence for AI and humans: code health scores, auto-generated docs, git analytics, dead code detection, and architectural decisions via MCP. This page is an auto-generated, always-fresh map of the nehant14/repowise repository, written primarily in python. Repowise indexes the source, parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the resulting architectural decisions into a wiki you can read or query through MCP.
The codebase has 2,903 source files, 22,832 symbols, and 10 languages, structured as a monorepo with 8 packages. Git churn analysis flags 429 high-frequency files as hotspots — places where bugs, rewrites, and code review tend to concentrate. The dependency graph clusters into 290 tightly-coupled module communities.
Use the panels above to open the interactive dashboards, or connect this repo to your editor via the Repowise MCP server for grounded answers inside Claude, Cursor, or VS Code.