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Contributed Reports

Real checkups make the scoring model better, but raw reports are too sensitive for public GitHub issues. Use the contributed-report format when you want to share a grade without sharing paths, secrets, customer data, or full local findings.

Validate Before Posting

python3 scripts/validate_contributed_report.py samples/contributed-report.json

The validator accepts only aggregate fields and fails closed when it sees raw user paths, emails, API-key shapes, bearer tokens, or other secret-shaped text.

Schema

This is an abridged example. See samples/contributed-report.json for a complete valid file with all 10 domain summaries.

{
  "schema": "claude-code-doctor-contributed-report-v1",
  "environment": {
    "os": "macOS",
    "harness": "Claude Code",
    "doctor_version": "v0.11.0",
    "audit_date": "2026-07-02"
  },
  "overall": {"grade": "B", "score": 72},
  "metrics": {
    "always_on_tokens": 18400,
    "permissions": 220,
    "mcp_tools": 31,
    "critical_findings": 0,
    "total_findings": 42
  },
  "domains": [
    {"name": "Directory structure", "grade": "B", "score": 74, "finding_count": 4, "red_flag_count": 0}
  ],
  "feedback": {
    "grade_felt": "about_right",
    "notes": "Aggregate feedback only."
  }
}

Rules:

  • Include exactly 10 domain summaries.
  • Use grades A through E and scores from 0 to 100.
  • Use non-negative integer counts for all metrics.
  • Keep notes general: no raw paths, emails, secrets, patient data, customer data, or full report excerpts.

Good Contribution

  • Overall grade and score.
  • OS family and harness.
  • Aggregate metrics: token load, permission count, MCP tool count, critical finding count, total finding count.
  • Per-domain grade, score, finding count, and red-flag count.
  • A short note about whether the grade felt too harsh, too soft, or about right.

Not For Public Issues

  • Full local reports.
  • tree output with real directories.
  • Raw action prompts containing local paths.
  • Secret-looking strings, emails, tokens, account IDs, patient data, or customer data.