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ilove323COMMUNITY
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metrics-review

Analyze product metrics to identify trends, anomalies, and prioritized insights.

1|Updated Mar 30, 2026
Search Tags:#metrics#dashboard#okr#retention#scorecard#trend-analysis#product-metrics
One-click install
npx skills add https://github.com/ilove323/comlan-skills --skill metrics-review-ilove323
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: metrics-review
Source: https://github.com/ilove323/comlan-skills/tree/main/product-management/skills/metrics-review
Command: npx skills add https://github.com/ilove323/comlan-skills --skill metrics-review-ilove323

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Product teams struggle to interpret raw metric tables and time series into clear, prioritized actions. This Skill converts disparate indicator values and trends into a concise review that highlights health, anomalies, and prioritized next steps so teams can decide what to investigate and what to act on.

Core Features & Use Cases

  • Trend analysis & anomaly detection: Compare current values to previous periods, targets, and baselines to surface meaningful changes.
  • Structured scorecard generation: Produce a compact L1/L2 metrics scorecard with status (healthy / risk / unmet) for quick stakeholder review.
  • Actionable recommendations: Provide hypothesis-driven root-cause suggestions, experiments to run, and monitoring or alerting steps.
  • Use case: Run a weekly metrics review to summarize DAU/MAU trends, retention cohorts, and conversion funnel shifts, then output a one-page brief with three prioritized actions.

Quick Start

Use the metrics-review skill to analyze last week's core product metrics, compare them to targets and the prior period, and return an executive summary with the top three recommended actions.

Frequently Asked Questions about metrics-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn raw product metrics into an actionable scorecard?▼

To turn product metrics into an actionable scorecard, compare current values against previous periods and targets to generate a structured status overview with prioritized follow-up actions for stakeholders.

What is the best way to analyze retention cohorts and conversion funnel shifts?▼

Analyzing retention cohorts and conversion funnel shifts requires time-series comparisons and segmentation breakdowns to surface meaningful changes and identify anomalies in your product metrics data.

How do I conduct a weekly metrics review for my product team?▼

Conduct a weekly metrics review by comparing core indicators like DAU/MAU to baselines, identifying anomalies, and outputting an executive summary with the top three prioritized recommended actions.

Can I generate hypothesis-driven root-cause suggestions from a metrics dashboard?▼

Yes, you can generate hypothesis-driven root-cause suggestions from a metrics dashboard by applying anomaly detection to time-series data and outputting recommended experiments and monitoring steps.

Do I need baseline and target values to investigate product metric anomalies?▼

Yes, investigating product metric anomalies requires explicit baseline and target values alongside time-series comparisons to accurately identify trends and generate prioritized actionable insights.

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