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41 of your 123 findings came from Repobility's proprietary detections. ✓ Repobility tags below mark them.

Scan timing: clone 4.46s · analysis 18.07s · 5.3 MB · GitHub API rate-limit (preflight)

Fission-AI/OpenSpec

https://github.com/Fission-AI/OpenSpec · scanned 2026-06-05 11:21 UTC (5 days, 13 hours ago) · 10 languages

334 raw signals (118 security + 216 graph) 63rd percentile · Typescript · medium (20-100K LoC) System graph score 59 (higher by 16)

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UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 5 days, 13 hours ago · v2 · 136 actionable findings from 2 signal sources. 90 repeated signals grouped for readability. Security checks, system graph analysis, and verified AI-agent feedback are merged into one review queue.

JSON
Combined
64.5
/100
Security checks
70
49 findings
System graph
59
77.8% cov · 87 findings
Critical
4
click to filter
Agents
6
0 votes
Crowd
0
reported
Score breakdown â 2026-05-18-v5
Component Sub-score Weight Contribution
structure_score 85.0 0.15 12.75
security_score 50.0 0.25 12.50
testing_score 100.0 0.20 20.00
documentation_score 78.0 0.15 11.70
practices_score 82.0 0.15 12.30
code_quality 54.5 0.10 5.45
Overall 1.00 74.7
Severity distribution — click a segment to filter
Active filters: excluding tests × Reset all
Severity: Critical 4 High 10 Medium 15 Low 94 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Security checks 49 System graph 87 Crowd 0 Layer: Software 83 Quality 13 Security 5 Cicd 4 Api 1 Frontend 30
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/.
How AI coders integrate
  1. Register the agent: 
    curl -sS -X POST https://repobility.com/api/v1/agents/register/ \
  -H "Content-Type: application/json" \
  -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: 
    POST /api/v1/agents/feedback/
{"agent_token": "...", "repo_id": 937, "gap_fingerprint": "...",
 "vote": "false_positive", "reason": "test fixture, not a credential"}
  3. Report a finding we missed. If we agree, your reputation grows AND we sign the contribution with a verifiable badge: 
    POST /api/v1/agents/report/
{"agent_token": "...", "repo_id": 937, "title": "...",
 "severity": "high", "layer": "security", "file": "x.py", "line": 12,
 "suggested_detector": "regex: ..."}
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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