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repowiseFaserF/ha-aegisbot

FaserF / ha-aegisbot

pythongithub.com/FaserF/ha-aegisbot
Indexed at5a9e090·1h ago·Up to date with upstream
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Code health

7.6out of 10Good

FaserF/ha-aegisbot scores 7.6 out of 10 on defect risk, which Repowise rates Good. Maintainability scores 8.7 out of 10. Static performance risk scores 9.9 out of 10. The three are scored separately and never blended into a single number. 6 of 49 files are git hotspots, the places where changes and bug fixes concentrate.

Full health report
Defect risk7.6/10 · Good
Maintainability8.7/10 · Excellent
Performance risk9.9/10 · Excellent
Files
49
Symbols
179
Modules
4
Doc pages
40
Dead exports
6

Where the risk concentrates

All 6 hotspots

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

FileChurnPrior fixesMaintainersCommits 90d
api.pycustom_components/aegisbot85.2th %ile22bus factor 13
version_manager.py.github/scripts77.8th %ile2411
config_flow.pycustom_components/aegisbot

Read more about FaserF/ha-aegisbot

  • 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
[![Code health](https://api.repowise.dev/badge/health/FaserF/ha-aegisbot.svg)](https://repowise.dev/repo/FaserF/ha-aegisbot)

How FaserF/ha-aegisbot works

This page is an auto-generated, always-fresh map of the FaserF/ha-aegisbot 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 49 source files, 179 symbols, and 6 languages, organised into 4 modules, led by python, yaml, json. Static analysis leaves 119 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.

96.3th %ile
1
2
6
generate_changelog.pyscripts92.6th %ile12bus factor 15
calculate_release_details.py.github/scripts81.5th %ile1311
update_templates.py.github/scripts88.9th %ile028
  • 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