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justadm / memory-bank

Simple agent memory service built with FastAPI and PostgreSQL

Pythongithub.com/justadm/memory-bank
Indexed at132425e·4d ago·Up to date with upstream
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Code health

7.0out of 10Good

justadm/memory-bank scores 7.0 out of 10 on defect risk, which Repowise rates Good. Maintainability scores 8.5 out of 10. Static performance risk scores 9.7 out of 10. The three are scored separately and never blended into a single number. 27 of 176 files are git hotspots, the places where changes and bug fixes concentrate.

Full health report
Defect risk7.0/10 · Good
Maintainability8.5/10 · Excellent
Performance risk9.7/10 · Excellent
Files
176
Symbols
1.3k
Modules
33
Doc pages
220
Dead exports
11

Where the risk concentrates

All 27 hotspots

Ranked by prior bug fixes and change frequency, mined from the full git history rather than from the code alone.

FileChurnPrior fixesMaintainersCommits 90d
test_api.pytests99.2th %ile01bus factor 19
lint_memory_query_inventory.pyscripts98.5th %ile01bus factor 116
test_memory_query_inventory.pytests

Read more about justadm/memory-bank

  • 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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Average health across every file, straight from the latest index.

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How justadm/memory-bank works

Simple agent memory service built with FastAPI and PostgreSQL This page is an auto-generated, always-fresh map of the justadm/memory-bank 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 176 source files, 1,316 symbols, and 8 languages, organised into 33 modules, led by python, markdown, shell. Static analysis leaves 608 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.

97.7th %ile
0
1bus factor 1
15
test_deploy_assets.pytests96.9th %ile01bus factor 113
service.pymemlayer_connector95.4th %ile01bus factor 18
memory_service.pyapp/services94.7th %ile01bus factor 16
  • CommitsChange-risk ranked history with AI-agent provenance and hotspots
  • ContributorsBus-factor, per-file maintainer maps, and human/agent collaboration
  • DecisionsArchitectural decisions extracted from commits and PRs
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