google / adk-python
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Code health
google/adk-python scores 7.2 out of 10 on defect risk, which Repowise rates Good. Maintainability scores 8.3 out of 10. Static performance risk scores 9.9 out of 10. The three are scored separately and never blended into a single number. 238 of 2,369 files are git hotspots, the places where changes and bug fixes concentrate.
Full health report- Files
- 2.4k
- Symbols
- 24k
- Modules
- 9
- Doc pages
- 2.7k
- Dead exports
- 155
Where the risk concentrates
All 238 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 |
|---|---|---|---|---|
| test_artifact_service.pytests/unittests/artifacts | 99.9th %ile | 10bug magnet | 6 | 11 |
| test_agent_tool.pytests/unittests/tools | 99.7th %ile | 8bug magnet | 4 | 9 |
Read more about google/adk-python
- 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/google/adk-python)Code health badge
Average health across every file, straight from the latest index.
[](https://repowise.dev/repo/google/adk-python)How google/adk-python works
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. This page is an auto-generated, always-fresh map of the google/adk-python 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 2,369 source files, 24,391 symbols, and 10 languages, organised into 9 modules, led by python, markdown, json. Static analysis leaves 8,641 open findings across the three health dimensions.
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