القائمة
Pre-launch health check that blocks you from shipping broken AI features. Grades 6 dimensions (model selection, data quality, cost, monitoring, failure UX, optimization).
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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| name | ai-health-check |
| description | Pre-launch health check that blocks you from shipping broken AI features. Grades 6 dimensions (model selection, data quality, cost, monitoring, failure UX, optimization). |
Before you ship an AI feature, it needs to pass 6 checks.
Most AI products fail because PMs skip the basics: no cost model, broken failure UX, terrible data quality. This skill stops you from launching garbage.
When this skill is invoked, start with:
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AI HEALTH CHECK
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Before shipping an AI feature, it needs to pass 6 checks.
What AI feature are you preparing to launch?
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/ai-health-check [feature-name]
Examples:
/ai-health-check "AI product recommendations" - Audit specific feature/ai-health-check "email composer AI" - Manual description/ai-health-check --pre-launch - Full checklist for current sprint| Dimension | What It Checks |
|---|---|
| Model Selection | Did you try simple approaches first? |
| Data Quality | The thing you're probably ignoring |
| Cost Modeling | Can you afford this at scale? |
| Production Monitoring | How will you know if it breaks? |
| Failure UX | What happens when AI screws up? |
| System Optimization | Are you measuring the right things? |
| Condition | Verdict |
|---|---|
| Any Blocker | DON'T SHIP |
| 2+ Risks (no blockers) | NEEDS WORK |
| 0-1 Risks | READY |
AI Health Check: Email Composer
Overall Readiness: NEEDS WORK (4/6 dimensions ready)
---
Ready: Model Selection, Production Monitoring, System Optimization
Risk: Data Quality, Failure UX
Blocker: Cost Modeling
VERDICT: DON'T SHIP YET
You have 1 blocker:
- No cost model -> Run /ai-cost-check RIGHT NOW
You have 2 risks:
- Data quality strategy undefined
- Failure UX is broken ("Something went wrong" isn't helpful)
---
What To Do Now:
Option A: Fix everything (RECOMMENDED)
1. Run /ai-cost-check (10 min)
2. Define data quality strategy (2 hours)
3. Build better failure UX (3 hours)
4. Rerun /ai-health-check
Option B: Ship with known risks
1. Fix the blocker only
2. Ship knowing data quality and failure UX are weak
3. Plan to fix in week 1
Cost Modeling missing:
"You're about to launch with zero idea if this bankrupts you at scale." Run
/ai-cost-checkfirst.
Failure UX broken:
"Something went wrong" tells users nothing. No confidence indicators = users don't know when to trust the AI.
No monitoring plan:
"Launching without monitoring = flying blind."
/ai-cost-check - Detailed cost modeling (run if cost dimension is blocked)/start-evals - Set up quality testing/four-risks - Overall feature risk assessmentBest for: Pre-launch validation of AI features Key insight: "Fine-tuning is the last resort. Data quality beats tool selection. Most AI failures are UX problems."