Measure Dashboard Requirements

Organization

product-on-purpose

measure-dashboard-requirements

Specifies what questions a dashboard must answer and the metrics, visualizations, filters, and data sources it needs, so data teams build something that informs decisions rather than displaying numbers. Use when requesting a dashboard or formalizing ad-hoc reporting. For the event tracking that feeds the dashboard, use measure-instrumentation-spec instead; instrument first, visualize second.

Overview

Publisher	product-on-purpose
Repository	`pm-skills`
Skill name	`measure-dashboard-requirements`
Stars	717
Forks	92
Bundled files	4
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by product-on-purpose on GitHub. Read the source before you install it.

Installation

Install the Measure Dashboard Requirements AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/product-on-purpose/pm-skills/tree/main/skills/measure-dashboard-requirements
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/product-on-purpose/pm-skills/tree/main/skills/measure-dashboard-requirements

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/product-on-purpose/pm-skills.git /tmp/pm-skills
mkdir -p .claude/skills
cp -r /tmp/pm-skills/skills/measure-dashboard-requirements .claude/skills/measure-dashboard-requirements

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Measure Dashboard Requirements in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Measure Dashboard Requirements on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Measure Dashboard Requirements is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Dashboard Requirements

A dashboard requirements document specifies what questions a dashboard should answer, what metrics it displays, and how data should be visualized. Clear requirements help data teams build dashboards that actually inform decisions rather than just displaying numbers.

When to Use

When requesting a new dashboard from data/analytics teams
To define KPI tracking for a product, feature, or team
When formalizing ad-hoc reporting into a persistent dashboard
Before quarterly planning to specify what visibility you need
When onboarding stakeholders who need self-serve analytics

When NOT to Use

You need the event tracking that feeds dashboards -> use measure-instrumentation-spec; instrument first, visualize second
You are designing an experiment readout, not a standing dashboard -> use measure-experiment-design and measure-experiment-results
You want OKR progress scored at cycle close -> use measure-okr-grader
The questions the dashboard should answer are not yet agreed -> frame outcomes first with foundation-okr-writer or define-problem-statement

Instructions

When asked to specify dashboard requirements, follow these steps:

Define the Purpose Start with the questions this dashboard should answer, not the charts it should show. What decisions will this dashboard inform? A dashboard without clear purpose becomes a vanity metrics display.
Identify the Audience Specify who will use this dashboard, how often, and in what context. An executive weekly review has different needs than a team's daily standup board.
Specify Key Metrics For each metric, document: name, business definition (in plain language), calculation formula, data source, and baseline/target values. Ambiguous metrics lead to misaligned dashboards.
Design Visualizations Recommend chart types based on what the data should communicate. Time trends need line charts; comparisons need bar charts; compositions need pie/treemaps. Include dimension breakdowns.
Define Filters and Segments Specify what drill-downs users need: date ranges, user segments, product areas, geographic regions. Anticipate the "slice and dice" questions users will ask.
Document Data Sources Identify where data comes from and any known data quality issues. Note latency requirements.does the dashboard need real-time data or is daily refresh sufficient?
Set Permissions and Access Determine who can view what. Some metrics may need restricted access. Consider both security requirements and organizational politics.

Output Format

Use the template in references/TEMPLATE.md to structure the output. A complete spec fills every template section: Overview; Purpose and Questions; Audience; Key Metrics; Visualization Specifications; Filters and Segments; Data Sources; Access and Permissions; Alerts and Thresholds; Acceptance Criteria; Open Questions; and Appendix.

Quality Checklist

Before finalizing, verify:

Purpose is framed as questions to answer, not charts to build
All metrics have clear definitions and calculation formulas
Data sources are identified and accessible
Visualization choices match the type of insight needed
Filters enable the drill-downs users will want
Refresh frequency matches decision-making cadence

Examples

See references/EXAMPLE.md for a completed example.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Measure Dashboard Requirements AI skill do?

Why use Measure Dashboard Requirements on TypingMind?

Because you install it once and use it with any model. Measure Dashboard Requirements is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Measure Dashboard Requirements in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/product-on-purpose/pm-skills/tree/main/skills/measure-dashboard-requirements. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Measure Dashboard Requirements?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Measure Dashboard Requirements?

As many as you like. As long as a model supports skills, you can use Measure Dashboard Requirements with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Measure Dashboard Requirements AI skill free?

Yes. It is published on GitHub by product-on-purpose under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Dashboard Requirements

When to Use

When NOT to Use

Instructions

Output Format

Quality Checklist

Examples

Bundled files

Frequently asked questions

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