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anthropics/courses

https://github.com/anthropics/courses · scanned 2026-05-16 00:51 UTC (2 weeks, 6 days ago) · 10 languages

19 findings (3 legacy + 16 scanner) 34th percentile · Python · tiny (<2K LoC) Scanner says 93 (lower by 36)

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 weeks, 6 days ago · v1 · 3 findings from 1 source. 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 2026-05-14-v3
Component Sub-score Weight Contribution
structure_score 55.0 0.15 8.25
security_score 100.0 0.25 25.00
testing_score 0.0 0.20 0.00
documentation_score 70.0 0.15 10.50
practices_score 40.0 0.15 6.00
code_quality 78.3 0.10 7.83
Overall 1.00 57.6
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Scan summary Repository scanned at 93.3/100 with 88.9% coverage. It contains 63 nodes across 0 cross-layer flows, written primarily in mixed languages. Engine surfaced 0 findings. Risk profile is low: 0 critical, 0 high, 0 medium. Recommended next step: open the software layer findings first — that's where the highest-impact wins live.

Showing 1 of 3 findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

high Legacy quality quality conf 0.86 Duplicated implementation block across source files
Duplicated blocks are a common artifact when generated code is pasted or recreated instead of reused. They increase maintenance cost because every future bug fix must be found in multiple locations.
prompt_engineering_interactive_tutorial/Anthropic 1P/hints.py:1 qualitylegacy
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