weboftrust / keripy
Key Event Receipt Infrastructure - the spec and implementation of the KERI protocol
Code health
weboftrust/keripy scores 5.4 out of 10 on defect risk, which Repowise rates Fair. Maintainability scores 6.5 out of 10. Static performance risk scores 10.0 out of 10. The three are scored separately and never blended into a single number. 80 of 531 files are git hotspots, the places where changes and bug fixes concentrate.
Full health report- Files
- 531
- Symbols
- 4.5k
- Modules
- 10
- Doc pages
- 613
- Dead exports
- 28
Where the risk concentrates
All 80 hotspotsRanked by prior bug fixes and change frequency, mined from the full git history rather than from the code alone.
| File | Churn | Prior fixes | Maintainers | Commits 90d |
|---|---|---|---|---|
| eventing.pysrc/keri/core | 99.2th %ile | 20bug magnet | 6 | 41 |
| habbing.pysrc/keri/app | 99.7th %ile | 13bug magnet | 6 | 49 |
Read more about weboftrust/keripy
- OverviewFiles, symbols, languages, packages, git intelligence
- ArchitectureDependency graph, layered architecture, symbol index, and third-party dependencies
- Code healthPer-file health scores, hotspots, test coverage, dead code, and refactoring targets
- AI explanationsProModule-by-module documentation generated from source
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[](https://repowise.dev/repo/weboftrust/keripy)Code health badge
Average health across every file, straight from the latest index.
[](https://repowise.dev/repo/weboftrust/keripy)How weboftrust/keripy works
Key Event Receipt Infrastructure - the spec and implementation of the KERI protocol This page is an auto-generated, always-fresh map of the weboftrust/keripy 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 531 source files, 4,471 symbols, and 9 languages, organised into 10 modules, led by python, json, shell. Static analysis leaves 5,661 open findings across the three health dimensions.
Use the links 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.