product-health-analysis

# Product Health Analysis Skill Transform raw metrics data into a clear health narrative — what's working, what's not, and what needs immediate attention. ## Required Inputs Ask the user for these if not provided: - **Metrics data** (current values for key metrics — even rough numbers work) - **Targets or benchmarks** (OKR targets, historical baselines, or industry benchmarks) - **Period** (week / month / quarter being analysed) - **Product area or segment** (are we looking at the whole product or a specific feature?) ## Metrics Framework Analyse across four layers: 1. **Acquisition** — new users, source quality, CAC trends 2. **Activation** — time to first value, onboarding completion rates 3. **Engagement** — DAU/MAU, feature adoption, session depth 4. **Retention** — D1/D7/D30 retention, churn rate, resurrection rate ## Process 1. For each metric, compare: current period vs. previous period, current vs. target 2. Flag anything more than 10% off target as requiring investigation 3. Look for correlations — does a drop in activation explain a retention dip 2 weeks later? 4. Write a plain-English health summary (no jargon) suitable for sharing with non-data stakeholders 5. Recommend top 3 areas for immediate investigation with suggested diagnostic steps 6. **Validate** — Confirm every flagged metric has a plausible root cause hypothesis, not just a raw number, and every recommended action has a specific owner or team ## Output Structure ### Product Health Report — [Peri...