cognicore-dev / cognicore-my-openenv
Memory operating system for AI agents — persistent memory, BM25 search, atomic decomposition, reflection engine, immune system. Zero API calls. 89% fewer tokens than alternatives. MCP + LangChain + OpenAI SDK.
Code health
cognicore-dev/cognicore-my-openenv scores 8.0 out of 10 on defect risk, which Repowise rates Good. Maintainability scores 8.6 out of 10. Static performance risk scores 9.8 out of 10. The three are scored separately and never blended into a single number. 21 of 506 files are git hotspots, the places where changes and bug fixes concentrate.
Full health report- Files
- 506
- Symbols
- 4.5k
- Modules
- 79
- Doc pages
- 742
- Dead exports
- 52
Where the risk concentrates
All 21 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 |
|---|---|---|---|---|
| remote.pycognicore/extension | 99.6th %ile | 9bug magnet | 1bus factor 1 | 19 |
| cli.pycognicore | 99.8th %ile | 4 | 3 | 6 |
| sqlite_backend.py |
Read more about cognicore-dev/cognicore-my-openenv
- 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/cognicore-dev/cognicore-my-openenv)Code health badge
Average health across every file, straight from the latest index.
[](https://repowise.dev/repo/cognicore-dev/cognicore-my-openenv)How cognicore-dev/cognicore-my-openenv works
Memory operating system for AI agents — persistent memory, BM25 search, atomic decomposition, reflection engine, immune system. Zero API calls. 89% fewer tokens than alternatives. MCP + LangChain + OpenAI SDK. This page is an auto-generated, always-fresh map of the cognicore-dev/cognicore-my-openenv 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 506 source files, 4,497 symbols, and 7 languages, organised into 79 modules, led by python, markdown, yaml. Static analysis leaves 1,569 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.