topoteretes / cognee
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine.
Code health
topoteretes/cognee scores 7.1 out of 10 on defect risk, which Repowise rates Good. Maintainability scores 8.4 out of 10. Static performance risk scores 9.8 out of 10. The three are scored separately and never blended into a single number. 298 of 2,262 files are git hotspots, the places where changes and bug fixes concentrate.
Full health report- Files
- 2.3k
- Symbols
- 13k
- Modules
- 172
- Doc pages
- 0
- Dead exports
- 145
Where the risk concentrates
All 298 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 |
|---|---|---|---|---|
| adapter.pycognee/infrastructure/databases/graph/ladybug | 99.9th %ile | 17 | 4 | 37 |
| server.pycognee-mcp/src | 99.7th %ile | 13 | 10 | 20 |
| closing_lru_cache.pycognee/infrastructure/databases/utils |
Read more about topoteretes/cognee
- 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/topoteretes/cognee)Code health badge
Average health across every file, straight from the latest index.
[](https://repowise.dev/repo/topoteretes/cognee)How topoteretes/cognee works
Cognee is the open-source AI memory platform for agents. Give your AI agents persistent long-term memory across sessions with a self-hosted knowledge graph engine. This page is an auto-generated, always-fresh map of the topoteretes/cognee 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 2,262 source files, 13,146 symbols, and 9 languages, organised into 172 modules, led by python, typescript, yaml. Static analysis leaves 6,369 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.