菜单
Diagnose why an AI feature is underperforming, hallucinating, or behaving inconsistently. Uses 4D audit to work backwards from symptoms to root cause.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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| name | ai-debug |
| description | Diagnose why an AI feature is underperforming, hallucinating, or behaving inconsistently. Uses 4D audit to work backwards from symptoms to root cause. |
Figure out why an existing AI feature is broken.
Works with:
When this skill is invoked, start with:
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AI DEBUG
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When AI fails, teams blame the model.
But 90% of failures are context failures.
What's going wrong?
1. Provide a Linear issue ID
2. Describe the symptoms
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/ai-debug # Describe symptoms manually
/ai-debug LIN-123 # Start from Linear bug/issue
Works backwards from symptoms to root cause using the 4D audit:
| Symptom | Likely Root Cause | Focus Area |
|---|---|---|
| Hallucinations | Missing domain context, no grounding | D2, D4 |
| Inconsistency | Vague job definition, missing rules | D1, D4 |
| Generic outputs | Missing user/environment context | D2 |
| Wrong tone/format | Missing constraints, no examples | D1, D4 |
| Slow responses | Too much context, bad discovery | D2, D3 |
| High costs | Dumping everything in prompt | D2, D3 |
| Demo vs prod mismatch | Discovery strategy broken | D3, D4 |
Key insight: When AI fails, teams blame the model. But 90% of failures are context failures.
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CONTEXT AUDIT COMPLETE
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Feature: [Name]
Symptoms: [What was reported]
D1 Demand: [CLEAR / GAP / CRITICAL]
D2 Data: [CLEAR / GAP / CRITICAL]
D3 Discovery: [CLEAR / GAP / CRITICAL]
D4 Defense: [CLEAR / GAP / CRITICAL]
Primary Issue: [Root cause summary]
RECOMMENDED FIXES (prioritized):
1. [Highest impact fix]
2. [Second fix]
3. [Third fix]
Quick Win: [Smallest change that would help]
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Questions to ask at each step:
Framework: 4D Context Canvas (Aakash Gupta & Miqdad Jaffer) Best for: Debugging hallucinations, inconsistency, performance issues in AI features