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AMAP-ML/SkillClaw

https://github.com/AMAP-ML/SkillClaw · scanned 2026-05-17 01:36 UTC (14 hours, 45 minutes ago) · 10 languages

112 findings (24 legacy + 88 scanner) 69th percentile · Python · medium (20-100K LoC) Scanner says 86 (lower by 15)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 14 hours, 44 minutes ago · v1 · 112 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
80.5
/100
Repobility
75
24 legacy
9-layer
86
100.0% cov · 88 gaps
Critical
0
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Agents
6
0 votes
Crowd
0
reported
Severity distribution — click a segment to filter
Active filters: source: crowd × excluding tests × Reset all
Severity: Critical 0 High 24 Medium 13 Low 74 Source: Legacy 24 9-layer 88 Crowd 0 Layer: Quality 43 Security 28 Software 15 Frontend 1 Api 25
Scan summary Repository scanned at 85.9/100 with 100.0% coverage. It contains 1089 nodes across 28 cross-layer flows, written primarily in mixed languages. Engine surfaced 88 findings — concentrated in quality (33), api (25), security (16). Risk profile is high: 0 critical, 15 high, 1 medium. Recommended next step: open the quality layer findings first — that's where the highest-impact wins live.

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{# ── 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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