← Back to list

fairness-audit
by do-ops885
Dermatology GOAP Orchestrator
⭐ 0🍴 0📅 Jan 25, 2026
SKILL.md
name: fairness-audit description: Validates True Positive Rate and False Positive Rate gaps across demographics using AgentDB metrics license: MIT compatibility: opencode metadata: audience: developers workflow: clinical-pipeline
What I do
I validate that the risk assessment meets fairness standards by checking TPR (True Positive Rate) and FPR (False Positive Rate) gaps across demographic groups. I ensure the model performs equitably regardless of skin tone.
When to use me
Use this when:
- Risk assessment is complete and you need fairness validation
- You need to verify TPR/FPR gaps are within acceptable thresholds
- You're ensuring the model doesn't exhibit demographic bias
Key Concepts
- TPR Gap: Difference in true positive rates across groups
- FPR Gap: Difference in false positive rates across groups
- Fairness Thresholds: Maximum acceptable gaps (typically 0.1)
- fairness_validated: State flag after audit complete
Source Files
services/agentDB.ts: Fairness metrics storageservices/goap.ts: Fairness validation action
Code Patterns
- Query AgentDB for demographic performance metrics
- Calculate TPR and FPR gaps between groups
- Fail validation if gaps exceed thresholds
Operational Constraints
- TPR and FPR gaps MUST be within acceptable thresholds
- If fairness validation fails, diagnosis is not web-verified
- Must maintain demographic parity in performance metrics
Score
Total Score
50/100
Based on repository quality metrics
✓SKILL.md
SKILL.mdファイルが含まれている
+20
○LICENSE
ライセンスが設定されている
0/10
○説明文
100文字以上の説明がある
0/10
○人気
GitHub Stars 100以上
0/15
○最近の活動
3ヶ月以内に更新がある
0/10
○フォーク
10回以上フォークされている
0/5
✓Issue管理
オープンIssueが50未満
+5
✓言語
プログラミング言語が設定されている
+5
○タグ
1つ以上のタグが設定されている
0/5
Reviews
💬
Reviews coming soon