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anthropics/financial-services

https://github.com/anthropics/financial-services · scanned 2026-05-15 21:01 UTC (2 weeks, 6 days ago) · 10 languages

17 findings (2 legacy + 15 scanner) 29th percentile · Python · small (2-20K LoC) Scanner says 98 (lower by 38)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 2 weeks, 6 days ago · v1 · 2 findings from 1 source. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

JSON
Combined
82.1
/100
Repobility
67
2 legacy
9-layer
98
88.9% cov · 0 gaps
Critical
0
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-14-v3
Component Sub-score Weight Contribution
structure_score 40.0 0.15 6.00
security_score 100.0 0.25 25.00
testing_score 0.0 0.20 0.00
documentation_score 74.6 0.15 11.19
practices_score 65.0 0.15 9.75
code_quality 80.0 0.10 8.00
Overall 1.00 59.9
Severity distribution — click a segment to filter
Active filters: search: "fragile-runtime" × excluding tests × Reset all
Severity: Critical 0 High 0 Medium 0 Low 1 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 2 9-layer 0 Crowd 0 Layer: Quality 2
Scan summary Repository scanned at 97.6/100 with 88.9% coverage. It contains 638 nodes across 1 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.

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