How does the skill handle performance drops?

It automatically flags any metric deviating more than 10% from the target as requiring investigation and provides a root cause hypothesis for each flag.

How does it help with diagnostic steps?

For every area requiring investigation, the skill suggests specific diagnostic steps and identifies necessary team owners to resolve the issue.

Do I need to provide clean data for the analysis?

No, the skill is designed to work with even rough numbers or raw data provided in the prompt to generate a structured directional report.

Is the output suitable for sharing with executives?

Yes, the skill produces a structured report written in plain English, avoiding data jargon to ensure it is suitable for non-technical stakeholders.

What metrics does this skill analyze?

The skill analyzes metrics across four key layers: Acquisition (new users), Activation (onboarding), Engagement (usage depth), and Retention (churn and return rates).

Product Health Analysis

Name: Product Health Analysis
Author: mohitagw15856

bymohitagw15856

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295

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分析与监控

Transforms raw product metrics into actionable health reports with RAG status, trend analysis, and root cause hypotheses.

The Product Health Analysis skill streamlines the data interpretation process for product managers and developers by converting raw metrics into a structured narrative. It evaluates product performance across four critical layers—acquisition, activation, engagement, and retention—comparing current values against historical baselines or OKR targets. By identifying correlations and generating root cause hypotheses for performance gaps, it provides a clear roadmap for immediate investigation and data-driven decision-making.

主要功能

01Stakeholder-ready health reports written in plain English for non-technical teams

02295 GitHub stars

03Correlation mapping to identify how shifts in one metric impact downstream performance

04Multi-layer analysis covering acquisition, activation, engagement, and retention metrics

05Root cause hypothesis generation for any metric deviating more than 10% from targets

06Automated RAG (Red-Amber-Green) status generation based on performance targets

使用场景

01Investigating performance issues or sudden drops in user retention and engagement

02Evaluating product-market fit signals during new feature launches or iterations

03Generating weekly or monthly product health reports for executive stakeholders

主要功能

01Stakeholder-ready health reports written in plain English for non-technical teams

02295 GitHub stars

03Correlation mapping to identify how shifts in one metric impact downstream performance

04Multi-layer analysis covering acquisition, activation, engagement, and retention metrics

05Root cause hypothesis generation for any metric deviating more than 10% from targets

06Automated RAG (Red-Amber-Green) status generation based on performance targets

使用场景

01Investigating performance issues or sudden drops in user retention and engagement

02Evaluating product-market fit signals during new feature launches or iterations

03Generating weekly or monthly product health reports for executive stakeholders