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Agent skill

Product Metrics Dashboard Design

by phuryn in phuryn/pm-skills

Designs a product metrics dashboard: a North Star and input metrics, a definition table with data sources, chart types and alert thresholds, and a screen layout.

MITAuto-check passedProduct & Project Management

Install Product Metrics Dashboard Design

skills CLI
$ npx skills add phuryn/pm-skills --skill metrics-dashboard -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install phuryn/pm-skills metrics-dashboard --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/phuryn/pm-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/pm-product-discovery/skills/metrics-dashboard .claude/skills/metrics-dashboard && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
metrics-dashboard
GitHub stars
27k
Token cost
~1.3k tokens
SKILL.md length
477 words
Files
1
Skills in repo
67
Repo updated
First seen
Licence
MIT

At a glance

Designs a product metrics dashboard: a North Star and input metrics, a definition table with data sources, chart types and alert thresholds, and a screen layout.

  • Works in 6 steps: Identify the metrics framework —… → For each metric, define → Design the dashboard layout → …
  • Creating a product metrics dashboard from scratch
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Defining KPIs and a North Star Metric for a product team

What it does

This skill has the agent design a metrics dashboard for a product you name, reading any existing dashboards, analytics data, OKRs or strategy docs you provide first. It organizes metrics into layers: one North Star Metric, three to five input metrics that drive it, health metrics that act as guardrails, and business metrics covering revenue, cost and unit economics.

For each metric it fills in a table with the exact definition, data source, visualization type, target and alert threshold, then lays out the dashboard. The background section draws on Ben Yoskovitz's Lean Analytics: four criteria for a good metric, the split between vanity and actionable and between leading and lagging metrics, and five steps for auditing the metrics you already track.

When your agent uses it

  • Creating a product metrics dashboard from scratch
  • Defining KPIs and a North Star Metric for a product team
  • Auditing an existing dashboard for vanity metrics
  • Setting alert thresholds as part of a data monitoring plan

Example prompts

  • “Design a metrics dashboard for our mobile habit-tracking app, starting from the OKRs in okrs.md.”
  • “Audit our current dashboard for vanity metrics and tell me which leading indicators are missing.”
  • “Define a North Star Metric and input metrics for our B2B invoicing product.”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Identify the metrics framework — organize metrics into layers
  2. For each metric, define
  3. Design the dashboard layout
  4. Set review cadence
  5. Define alerts
  6. Recommend tools based on the user's context

What it can do on your machine

Read from SKILL.md and the folder at commit 6058e29. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • productcompass.pm

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Product Metrics Dashboard Design loads about 1.3k tokens when it runs. Until then it costs about 65 tokens; SKILL.md has 477 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from phuryn/pm-skills at commit 6058e29, republished under its MIT licence (© phuryn). 477 words, ~1,282 tokens.

Download SKILL.mdSave it as .claude/skills/metrics-dashboard/SKILL.md (or your agent's skills folder).
name
metrics-dashboard
description
Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.

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

Show full SKILL.md (275 more words)Show less
Instructions

  1. 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

  2. For each metric, define:

    MetricDefinitionData SourceVisualizationTargetAlert 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]

  3. 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]        │
└─────────────────────────────────────────────┘

  4. 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

  5. Define alerts:

    • What thresholds trigger investigation?
    • Who gets alerted and through what channel?
    • What's the expected response time?

  6. 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

© phuryn, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in pm-product-discovery/skills/metrics-dashboard of phuryn/pm-skills.

Open the folder on GitHubat commit 6058e29

Compare with similar skills

Product Metrics Dashboard Design next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Product Metrics Dashboard Design compared with similar skills
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Product Metrics Dashboard Design this skillphuryn/pm-skills27k—~1.3kAutomated safety check: PassMIT
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Analytics Strategyrampstackco/claude-skills945—~2.4kAutomated safety check: PassMIT
Pm Metricsserejaris/personal-corp-os229—~3kAutomated safety check: PassMIT
Lumen Reconjeremylongshore/tons-of-skills-marketplace2.8k—~1.1kAutomated safety check: NotesMIT
Feature Analytics Instrumentation Plannermistralai/mistral-vibe5.1k—~2.2kAutomated safety check: PassApache-2.0

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Categories

Questions about Product Metrics Dashboard Design

What does Product Metrics Dashboard Design do?

Designs a product metrics dashboard: a North Star and input metrics, a definition table with data sources, chart types and alert thresholds, and a screen layout. This skill has the agent design a metrics dashboard for a product you name, reading any existing dashboards, analytics data, OKRs or strategy docs you provide first. It organizes metrics into layers: one North Star Metric, three to five input metrics that drive it, health metrics that act as guardrails, and business metrics covering revenue, cost and unit economics.

When should I use Product Metrics Dashboard Design?

Product Metrics Dashboard Design fits situations like: creating a product metrics dashboard from scratch; defining KPIs and a North Star Metric for a product team; auditing an existing dashboard for vanity metrics; setting alert thresholds as part of a data monitoring plan.

How do I install Product Metrics Dashboard Design in Claude Code?

Run `npx skills add phuryn/pm-skills --skill metrics-dashboard -a claude-code`. Or copy the skill folder (pm-product-discovery/skills/metrics-dashboard in phuryn/pm-skills) into .claude/skills/metrics-dashboard in your project. Claude Code loads it when a task matches its description.

How do I install Product Metrics Dashboard Design in Codex?

Run `npx skills add phuryn/pm-skills --skill metrics-dashboard -a codex`. Or copy the skill folder (pm-product-discovery/skills/metrics-dashboard in phuryn/pm-skills) into .agents/skills/metrics-dashboard in your project. Codex loads it when a task matches its description.

Can I use Product Metrics Dashboard Design in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add phuryn/pm-skills --skill metrics-dashboard -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/metrics-dashboard, .gemini/skills/metrics-dashboard, .github/skills/metrics-dashboard and .opencode/skills/metrics-dashboard in your project.

What does Product Metrics Dashboard Design need to run?

SKILL.md names no scripts, command-line tools or credentials: Product Metrics Dashboard Design is instructions for the agent only.

Does Product Metrics Dashboard Design access the network?

SKILL.md names 1 domain. As links in the text: productcompass.pm. This is read from the text; nothing was executed.

Is Product Metrics Dashboard Design safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Product Metrics Dashboard Design use?

Product Metrics Dashboard Design is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Product Metrics Dashboard Design use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Product Metrics Dashboard Design?

Skills that share tags, products or a category with Product Metrics Dashboard Design: Lens Metrics (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Analytics Strategy (rampstackco/claude-skills, 945 stars), Pm Metrics (serejaris/personal-corp-os, 229 stars) and Lumen Recon (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Product Metrics Dashboard Design?

phuryn (a GitHub user) maintains it in phuryn/pm-skills, which has 26,862 GitHub stars. The repository holds 67 skills in this directory. The repository was last updated on October 9, 2026.

Source: phuryn/pm-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.