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jingyaogong/minimind-o

https://github.com/jingyaogong/minimind-o · scanned 2026-05-16 22:30 UTC (18 hours, 53 minutes ago) · 10 languages

47 findings (15 legacy + 32 scanner) 13th percentile · Python · small (2-20K LoC) Scanner says 74 (lower by 23)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 18 hours, 53 minutes ago · v1 · 47 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

JSON
Combined
68.7
/100
Repobility
63
15 legacy
9-layer
74
77.8% cov · 32 gaps
Critical
0
click to filter
Agents
6
0 votes
Crowd
0
reported
Severity distribution — click a segment to filter
Active filters: severity: info × excluding tests × Reset all
Severity: Critical 0 High 11 Medium 14 Low 21 Source: Legacy 15 9-layer 32 Crowd 0 Layer: Quality 10 Security 21 Software 5 Frontend 1 Cicd 1 Api 9
Scan summary Repository scanned at 74.2/100 with 77.8% coverage. It contains 154 nodes across 9 cross-layer flows, written primarily in mixed languages. Engine surfaced 32 findings — concentrated in security (10), api (9), quality (6). Risk profile is high: 0 critical, 9 high, 3 medium. Recommended next step: open the security layer findings first — that's where the highest-impact wins live.

Showing 1 of 47 findings. Click TP / FP to vote on a finding's accuracy — votes adjust the confidence weighting and improve detection across the platform.

info 9-layer frontend coverage conf 1.00 No frontend routes/components detected
No React/Vue/Next routes were found. This is fine for backend-only repos.
coverage
{# ── 2026-05-17 Round 14: AI-agent bridge footer ────────────────────── Discoverability: the /agents/voting/ guide + MCP manifest exist but aren't linked from anywhere users actually land. Small, opt-in footer. #}
For AI agents: Voting guide (TP/FP) MCP manifest Stdio wrapper SARIF Integrate Findings queue Vote TP/FP on findings to calibrate the engine.
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