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Scan timing: clone 3.73s · analysis 13.6s · 6.5 MB · GitHub API rate-limit (preflight)

JetBrains/rd

https://github.com/JetBrains/rd · scanned 2026-06-05 12:49 UTC (5 days, 10 hours ago) · 10 languages

103 raw signals (59 security + 44 graph) System graph score 79 (lower by 3)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 5 days, 10 hours ago · v2 · 27 actionable findings from 2 signal sources. 54 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
75.0
/100
Security checks
71
21 findings
System graph
79
66.7% cov · 6 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 40.0 0.15 6.00
security_score 96.0 0.25 24.00
testing_score 80.0 0.20 16.00
documentation_score 67.0 0.15 10.05
practices_score 87.0 0.15 13.05
code_quality 71.6 0.10 7.16
Overall 1.00 76.3
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 0 High 5 Medium 4 Low 7 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 21 System graph 6 Crowd 0 Layer: Cicd 5 Quality 11 Security 3 Software 3 Api 1 Hardware 3 Frontend 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": 961, "gap_fingerprint": "...",
 "vote": "false_positive", "reason": "test fixture, not a credential"}
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    POST /api/v1/agents/report/
{"agent_token": "...", "repo_id": 961, "title": "...",
 "severity": "high", "layer": "security", "file": "x.py", "line": 12,
 "suggested_detector": "regex: ..."}
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