Scan timing: clone 3.06s · analysis 1.47s · 28.3 MB · GitHub preflight 409ms
https://github.com/zilliztech/claude-context.git
· scanned 2026-05-23 03:15 UTC (1 week, 6 days ago)
· 10 languages
196 findings (63 legacy + 133 scanner) 11/13 scanners ran 75th percentile · Typescript · small (2-20K LoC) Scanner says 87 (lower by 8)
Last scanned 1 week, 6 days ago · v2 · 130 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.
| Component | Sub-score | Weight | Contribution |
|---|---|---|---|
structure_score |
75.0 | 0.15 | 11.25 |
security_score |
100.0 | 0.25 | 25.00 |
testing_score |
51.0 | 0.20 | 10.20 |
documentation_score |
92.0 | 0.15 | 13.80 |
practices_score |
84.0 | 0.15 | 12.60 |
code_quality |
62.0 | 0.10 | 6.20 |
| Overall | 1.00 | 79.0 |
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.
evaluation/utils/format.py:191
evaluation/servers/read_server.py:266
evaluation/servers/read_server.py:181
evaluation/servers/read_server.py:132
evaluation/servers/grep_server.py:211
evaluation/run_evaluation.py:14
evaluation/analyze_and_plot_mcp_efficiency.py:102
python/test_endtoend.py:99
python/ts_executor.py:302
evaluation/retrieval/base.py:176
evaluation/analyze_and_plot_mcp_efficiency.py:54
evaluation/generate_subset_json.py:26
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