flamehaven01 / ai-slop-detector
Stop shipping AI slop. Detects empty functions, fake documentation, and inflated comments in AI-generated code. Production-ready.
Code health
flamehaven01/ai-slop-detector scores 8.3 out of 10 on defect risk, which Repowise rates Excellent. Maintainability scores 9.3 out of 10. Static performance risk scores 9.9 out of 10. The three are scored separately and never blended into a single number. 18 of 226 files are git hotspots, the places where changes and bug fixes concentrate.
Full health report- Files
- 226
- Symbols
- 2.2k
- Modules
- 11
- Doc pages
- 265
- Dead exports
- 15
Where the risk concentrates
All 18 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 |
|---|---|---|---|---|
| cli.pysrc/slop_detector | 99.4th %ile | 15bug magnet | 2 | 10 |
| core.pysrc/slop_detector | 97.1th %ile | 8bug magnet | 2 | 10 |
Read more about flamehaven01/ai-slop-detector
- 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/flamehaven01/ai-slop-detector)Code health badge
Average health across every file, straight from the latest index.
[](https://repowise.dev/repo/flamehaven01/ai-slop-detector)How flamehaven01/ai-slop-detector works
Stop shipping AI slop. Detects empty functions, fake documentation, and inflated comments in AI-generated code. Production-ready. This page is an auto-generated, always-fresh map of the flamehaven01/ai-slop-detector 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 226 source files, 2,190 symbols, and 10 languages, organised into 11 modules, led by python, markdown, typescript. Static analysis leaves 679 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.