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Scan timing: clone 1.36s · analysis 0.08s · GitHub preflight 402ms

elopezguti02/llm-response-evaluator

https://github.com/elopezguti02/llm-response-evaluator.git · scanned 2026-05-25 23:54 UTC (1 week, 3 days ago) · 10 languages

13 findings (3 legacy + 10 scanner) 70th percentile · Python · tiny (<2K LoC) Scanner says 85 (lower by 14)

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 week, 3 days ago · v2 · 8 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

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Score breakdown â 2026-05-18-v5
Component Sub-score Weight Contribution
structure_score 30.0 0.15 4.50
security_score 100.0 0.25 25.00
testing_score 70.0 0.20 14.00
documentation_score 55.0 0.15 8.25
practices_score 72.0 0.15 10.80
code_quality 80.0 0.10 8.00
Overall 1.00 70.5
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Bug-class explainers. Each card groups findings of the same shape — these are the patterns most likely to ship to prod and reappear in future scans unless you systematically fix the cause, not just the instance.

No integrity bug-classes triggered on this scan. The 6 classes we check for — fragile runtime, duplicates, orphan pages, legacy markers, commented-out code, config drift — have zero matches. Solid foundation.
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