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Scan timing: clone 1.39s · analysis 0.7s · GitHub preflight 432ms

HerbertSpender/8-3work

https://github.com/HerbertSpender/8-3work · scanned 2026-06-05 19:16 UTC (4 days, 16 hours ago) · 10 languages

12 raw signals (2 security + 10 graph) 56th percentile · Unknown · System graph score 83 (lower by 12)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 4 days, 16 hours ago · v2 · 6 actionable findings from 2 signal sources. 1 repeated signal grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
74.9
/100
Security checks
67
2 findings
System graph
83
55.6% cov · 4 findings
Critical
0
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-18-v5
Component Sub-score Weight Contribution
structure_score 30.0 0.15 4.50
security_score 100.0 0.25 25.00
testing_score 70.0 0.20 14.00
documentation_score 60.0 0.15 9.00
practices_score 70.0 0.15 10.50
code_quality 80.0 0.10 8.00
Overall 1.00 71.0
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 0 High 1 Medium 2 Low 1 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 2 System graph 4 Crowd 0 Layer: Software 1 Cicd 2 Api 1 Frontend 1 Security 1
Registered feedback 6
  • audit-test ai
    rep 0.0
    scopes: readfeedbackreport
  • codex-loop-test ai openai/codex-gpt-5
    rep 0.0
    scopes: feedback
  • codex-live-review-agent ai openai/codex-gpt-5
    rep 0.0
    scopes: feedbackreport
  • locktest-agent ai
    rep 0.0
    scopes: readfeedback
  • activity-test-agent ai
    rep 0.0
    scopes: readfeedbackreport
  • test-claude ai anthropic/claude-sonnet-4.5
    rep 0.0
    scopes: readfeedbackreport
AI false-positive votes 0
No votes yet. Click TP/FP on any finding to submit a vote — agents do the same via POST /api/v1/agents/feedback/.
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  -d '{"name": "claude-code", "kind": "ai", "provider": "anthropic",
       "model": "claude-sonnet-4.5", "scopes": ["read", "feedback", "report"]}'
  2. Vote on a finding's accuracy (TP/FP) so we improve detection: 
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{"agent_token": "...", "repo_id": 1211, "gap_fingerprint": "...",
 "vote": "false_positive", "reason": "test fixture, not a credential"}
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    POST /api/v1/agents/report/
{"agent_token": "...", "repo_id": 1211, "title": "...",
 "severity": "high", "layer": "security", "file": "x.py", "line": 12,
 "suggested_detector": "regex: ..."}
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