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repowiseimbue-ai/mngr

imbue-ai / mngr

CLI for managing coding agents

Python405github.com/imbue-ai/mngr
Indexed atc3adcc3·3h ago·Up to date with upstream
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Code health

6.9out of 10Good

imbue-ai/mngr scores 6.9 out of 10 on defect risk, which Repowise rates Good. Maintainability scores 8.2 out of 10. Static performance risk scores 9.7 out of 10. The three are scored separately and never blended into a single number. 389 of 2,766 files are git hotspots, the places where changes and bug fixes concentrate.

Full health report
Defect risk6.9/10 · Good
Maintainability8.2/10 · Excellent
Performance risk9.7/10 · Excellent
Files
2.8k
Symbols
36k
Modules
43
Doc pages
4.4k
Dead exports
199

Where the risk concentrates

All 389 hotspots

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

FileChurnPrior fixesMaintainersCommits 90d
app.pyapps/minds/imbue/minds/desktop_client99.9th %ile58bug magnet9155
main.jsapps/minds/electron99.8th %ile53bug magnet7105

Read more about imbue-ai/mngr

  • 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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Code health badge

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

Code health badge showing the average health score out of 10
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How imbue-ai/mngr works

CLI for managing coding agents This page is an auto-generated, always-fresh map of the imbue-ai/mngr 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 2,766 source files, 35,955 symbols, and 10 languages, organised into 43 modules, led by python, markdown, typescript. Static analysis leaves 7,597 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.

test_desktop_client.pyapps/minds/imbue/minds/desktop_client
99.9th %ile
21bug magnet
7
97
api_v1.pyapps/minds/imbue/minds/desktop_client99.8th %ile13bug magnet891
tui.pylibs/mngr_kanpan/imbue/mngr_kanpan99.7th %ile10bug magnet2bus factor 153
api_v1_test.pyapps/minds/imbue/minds/desktop_client99.6th %ile5bug magnet663
  • 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
  • Chat with this repoSign inProAsk grounded questions over the indexed code