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HKUDS/Vibe-Trading

https://github.com/HKUDS/Vibe-Trading · scanned 2026-07-23 19:48 UTC (1 month, 2 weeks ago) · 10 languages

172 raw signals (39 security + 133 graph) 61st percentile · Python · medium (20-100K LoC)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 1 month, 2 weeks ago · v6 · last Δ +6.0 (diff) · 159 actionable findings from 2 signal sources. 9 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
69.1
/100
Security checks
64
26 findings
System graph
74
100.0% cov · 133 findings
Critical
0
click to filter
Agents
10
0 votes
Crowd
0
reported
Score breakdown â 2026-05-17-v4 calibration-aware
Component Sub-score Weight Contribution
structure_score 60.0 0.15 9.00
security_score 58.3 0.25 14.57
testing_score 95.0 0.20 19.00
documentation_score 88.0 0.15 13.20
practices_score 75.0 0.15 11.25
code_quality 61.2 0.10 6.12
Overall 1.00 73.1
Calibrated penalty buckets (security_score): web: 1.6 · agent: 6.9 · authz: 8.4 · threat: 21.6 · journey: 3.3
Severity distribution — click a segment to filter
Active filters: search: "duplicates" × excluding tests × Reset all
Severity: Critical 0 High 24 Medium 73 Low 51 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 26 System graph 133 Crowd 0 Layer: Quality 86 Security 43 Cicd 3 Software 17 Frontend 6 Hardware 1 Dependencies 1 Api 2
Scan summary Repository scanned at 74.1/100 with 100.0% coverage. It contains 14060 nodes across 30 cross-layer flows, written primarily in mixed languages. Engine surfaced 133 findings — concentrated in quality (81), security (26), software (16). Risk profile is high: 0 critical, 12 high, 70 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

Showing 0 of 159 actionable findings. 168 raw detector signals were grouped into reader-sized issues. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

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