Metrics Dashboard
Pawel HurynCommunityCreated by Pawel Huryn
- Skill
- Content generator
- Business and productivity
- MIT
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides a systematic approach to building product metrics dashboards. It guides users through identifying a North Star Metric, selecting supporting input and health metrics, and mapping them to specific data sources and visualization types. The process emphasizes actionable data over vanity metrics and includes a framework for defining alert thresholds and review cadences to ensure the dashboard remains a useful tool for product decision-making.
What it does
- Organizes metrics into a hierarchical framework of North Star, Input, Health, and Business metrics.
- Provides a structured template for defining calculation methods, data sources, and visualization types for each metric.
- Offers a standardized dashboard layout design for clear data presentation.
- Establishes a review cadence to align metrics with operational, tactical, and strategic goals.
- Defines alert thresholds and response protocols for critical data changes.
- Recommends appropriate analytics and monitoring tools based on specific product needs.
When to use it
- When you need to define KPIs for a new product or feature.
- When you are setting up or auditing product analytics tracking.
- When you need to build a data monitoring plan to track product health.
- When you want to transition from tracking vanity metrics to actionable product insights.
Advantages
- Ensures metrics are actionable and behavior-changing rather than just descriptive.
- Provides a clear, repeatable structure for dashboard design.
- Balances high-level business goals with granular operational health monitoring.
- Helps teams establish a common language around product success.
Usage examples
- “Design a metrics dashboard for our new mobile e-commerce app.”
- The agent will generate a structured markdown document outlining the North Star Metric, key input levers, health guardrails, and a layout plan for tracking user conversion and revenue.
- “Help me define alert thresholds for our SaaS platform's churn rate.”
- The agent will guide you through setting specific thresholds based on historical data and define the appropriate response team and communication channel for alerts.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/phuryn/metrics-dashboard/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip metrics-dashboard.zip -d .agents/skills
Documentation by Pawel Huryn
Product Metrics Dashboard
Design a comprehensive product metrics dashboard with the right metrics, visualizations, and alert thresholds.
Context
You are designing a metrics dashboard for $ARGUMENTS.
If the user provides files (existing dashboards, analytics data, OKRs, or strategy docs), read them first.
Domain Context
Metrics vs KPIs vs NSM: Metrics = all measurable things. KPIs = a few key quantitative metrics tracked over a longer period. North Star Metric = a single customer-centric KPI that is a leading indicator of business success.
4 criteria for a good metric (Ben Yoskovitz, Lean Analytics): (1) Understandable — creates a common language. (2) Comparative — over time, not a snapshot. (3) Ratio or Rate — more revealing than whole numbers. (4) Behavior-changing — the Golden Rule: "If a metric won't change how you behave, it's a bad metric."
8 metric types: Vanity vs Actionable (only actionable metrics change behavior), Qualitative vs Quantitative (WHAT vs WHY — you need both; never stop talking to customers), Exploratory vs Reporting (explore data to uncover unexpected insights), Lagging vs Leading (leading indicators enable faster learning cycles, e.g. customer complaints predict churn).
5 action steps: (1) Audit metrics against the 4 good-metric criteria. (2) Update dashboards — ensure all key metrics are good ones. (3) Identify vanity metrics — be careful how you use them. (4) Classify leading vs lagging indicators. (5) Pick one problem and dig deep into the data.
For case studies and more detail: Are You Tracking the Right Metrics? by Ben Yoskovitz
Instructions
Identify the metrics framework — organize metrics into layers:
North Star Metric: The single metric that best captures core value delivery
Input Metrics (3-5): The levers that drive the North Star
Health Metrics: Guardrails that ensure overall product health
Business Metrics: Revenue, cost, and unit economics
For each metric, define:
Metric Definition Data Source Visualization Target Alert Threshold [Name] [Exact calculation: numerator/denominator, time window] [Where the data comes from] [Line chart / Bar / Number / Funnel] [Goal value] [When to trigger an alert] Design the dashboard layout:
┌─────────────────────────────────────────────┐ │ NORTH STAR: [Metric] — [Current Value] │ │ Trend: [↑/↓ X% vs last period] │ ├──────────────────┬──────────────────────────┤ │ Input Metric 1 │ Input Metric 2 │ │ [Sparkline] │ [Sparkline] │ ├──────────────────┼──────────────────────────┤ │ Input Metric 3 │ Input Metric 4 │ │ [Sparkline] │ [Sparkline] │ ├──────────────────┴──────────────────────────┤ │ HEALTH: [Latency] [Error Rate] [NPS] │ ├─────────────────────────────────────────────┤ │ BUSINESS: [MRR] [CAC] [LTV] [Churn] │ └─────────────────────────────────────────────┘Set review cadence:
Daily: Operational health (errors, latency, critical flows)
Weekly: Input metrics and engagement trends
Monthly: North Star, business metrics, OKR progress
Quarterly: Strategic review and metric recalibration
Define alerts:
What thresholds trigger investigation?
Who gets alerted and through what channel?
What's the expected response time?
Recommend tools based on the user's context:
Amplitude, Mixpanel, PostHog for product analytics
Looker, Metabase, Mode for SQL-based dashboards
Datadog, Grafana for operational health
Think step by step. Save the dashboard specification as a markdown document.
Further Reading
Files
- ATTRIBUTION.mdAdded by AutoGineer874 B
- LICENSELicence file added by AutoGineer1.0 KiB
- SKILL.md5.6 KiB
SKILL.md
Product Metrics Dashboard
Design a comprehensive product metrics dashboard with the right metrics, visualizations, and alert thresholds.
Context
You are designing a metrics dashboard for $ARGUMENTS.
If the user provides files (existing dashboards, analytics data, OKRs, or strategy docs), read them first.
Domain Context
Metrics vs KPIs vs NSM: Metrics = all measurable things. KPIs = a few key quantitative metrics tracked over a longer period. North Star Metric = a single customer-centric KPI that is a leading indicator of business success.
4 criteria for a good metric (Ben Yoskovitz, Lean Analytics): (1) Understandable — creates a common language. (2) Comparative — over time, not a snapshot. (3) Ratio or Rate — more revealing than whole numbers. (4) Behavior-changing — the Golden Rule: "If a metric won't change how you behave, it's a bad metric."
8 metric types: Vanity vs Actionable (only actionable metrics change behavior), Qualitative vs Quantitative (WHAT vs WHY — you need both; never stop talking to customers), Exploratory vs Reporting (explore data to uncover unexpected insights), Lagging vs Leading (leading indicators enable faster learning cycles, e.g. customer complaints predict churn).
5 action steps: (1) Audit metrics against the 4 good-metric criteria. (2) Update dashboards — ensure all key metrics are good ones. (3) Identify vanity metrics — be careful how you use them. (4) Classify leading vs lagging indicators. (5) Pick one problem and dig deep into the data.
For case studies and more detail: Are You Tracking the Right Metrics? by Ben Yoskovitz
Instructions
Identify the metrics framework — organize metrics into layers:
North Star Metric: The single metric that best captures core value delivery
Input Metrics (3-5): The levers that drive the North Star
Health Metrics: Guardrails that ensure overall product health
Business Metrics: Revenue, cost, and unit economics
For each metric, define:
Metric Definition Data Source Visualization Target Alert Threshold [Name] [Exact calculation: numerator/denominator, time window] [Where the data comes from] [Line chart / Bar / Number / Funnel] [Goal value] [When to trigger an alert] Design the dashboard layout:
┌─────────────────────────────────────────────┐ │ NORTH STAR: [Metric] — [Current Value] │ │ Trend: [↑/↓ X% vs last period] │ ├──────────────────┬──────────────────────────┤ │ Input Metric 1 │ Input Metric 2 │ │ [Sparkline] │ [Sparkline] │ ├──────────────────┼──────────────────────────┤ │ Input Metric 3 │ Input Metric 4 │ │ [Sparkline] │ [Sparkline] │ ├──────────────────┴──────────────────────────┤ │ HEALTH: [Latency] [Error Rate] [NPS] │ ├─────────────────────────────────────────────┤ │ BUSINESS: [MRR] [CAC] [LTV] [Churn] │ └─────────────────────────────────────────────┘Set review cadence:
Daily: Operational health (errors, latency, critical flows)
Weekly: Input metrics and engagement trends
Monthly: North Star, business metrics, OKR progress
Quarterly: Strategic review and metric recalibration
Define alerts:
What thresholds trigger investigation?
Who gets alerted and through what channel?
What's the expected response time?
Recommend tools based on the user's context:
Amplitude, Mixpanel, PostHog for product analytics
Looker, Metabase, Mode for SQL-based dashboards
Datadog, Grafana for operational health
Think step by step. Save the dashboard specification as a markdown document.
Further Reading
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Created by
- Pawel Huryn
- Publisher
- Pawel Huryn (Community)
- Source
- phuryn/pm-skills · pm-product-discovery/skills/metrics-dashboard · commit 2a12295
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Pawel Huryn or Pawel Huryn.
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Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download metrics-dashboard.zip