Files

T

mohitagw15856 513e1d3ce7 fix: sync all skill updates and new skills into plugin bundles

- Synced 97 existing skill SKILL.md files from skills/ to their plugin bundle copies
- Added 7 new skills to plugin bundles:
  - seo-content-brief, media-pitch -> pm-gtm
  - tax-planning-checklist -> pm-finance
  - change-management-plan -> pm-hr
  - sales-forecasting-model -> pm-sales
  - workshop-facilitation-guide -> pm-operations
  - teaching-lesson-plan -> pm-cross

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-04-20 21:00:08 +01:00

2.9 KiB

Raw Blame History

name, description

name	description
product-health-analysis	Interpret product metrics against goals and surface actionable signals. Use when asked to analyse product health, review key metrics, investigate a performance issue, produce a health report, or assess product-market fit signals. Produces a structured health report with RAG status, trend analysis, root cause hypotheses, and prioritised actions.

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:

Acquisition — new users, source quality, CAC trends
Activation — time to first value, onboarding completion rates
Engagement — DAU/MAU, feature adoption, session depth
Retention — D1/D7/D30 retention, churn rate, resurrection rate

Process

For each metric, compare: current period vs. previous period, current vs. target
Flag anything more than 10% off target as requiring investigation
Look for correlations — does a drop in activation explain a retention dip 2 weeks later?
Write a plain-English health summary (no jargon) suitable for sharing with non-data stakeholders
Recommend top 3 areas for immediate investigation with suggested diagnostic steps
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 — [Period]

Overall Health: 🟢 On Track / 🟡 Watch / 🔴 Action Required

Metric	Current	Target	vs. Last Period	Status
[metric]	[value]	[target]	[+/-%]	[🟢/🟡/🔴]

Key Observations: [3-5 bullet observations written in plain English]

Areas Requiring Investigation:

[Metric + hypothesis + suggested diagnostic]
[Metric + hypothesis + suggested diagnostic]
[Metric + hypothesis + suggested diagnostic]

Recommended Actions: [Specific next steps with owners and timelines]

Quality Checks

Every metric includes both a target and a trend (not just a snapshot)
At least one correlation is drawn between metrics (e.g., activation → retention)
Every flagged metric has a root cause hypothesis, not just "it dropped"
Observations are written for a non-technical stakeholder (no raw query language or data jargon)
Overall health rating is justified with specific evidence

2.9 KiB Raw Blame History