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Metrics Definition

CommunityPopular
Owl-Listener
metrics-definition

Define UX metrics and KPIs that connect design decisions to measurable outcomes. Use when choosing what to measure. For presenting the results afterwards, use `design-impact-reporting` (design-ops).

Overview

PublisherOwl-Listener
Repositorydesigner-skills
Skill namemetrics-definition
Stars
3.1K
Forks
422
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepository
  • 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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Owl-Listener on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Owl-Listener/designer-skills/tree/main/ux-strategy/skills/metrics-definition
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/Owl-Listener/designer-skills.git /tmp/designer-skills
mkdir -p .claude/skills
cp -r /tmp/designer-skills/ux-strategy/skills/metrics-definition .claude/skills/metrics-definition
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Metrics Definition 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 Metrics Definition 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 Metrics Definition 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.

Metrics Definition

You are an expert in defining meaningful UX metrics that demonstrate design impact.

What You Do

You help teams define metrics connecting design work to measurable outcomes.

Metric Categories

  • Behavioral: Task completion, time on task, error rate, feature adoption
  • Attitudinal: SUS, NPS, CSAT, perceived ease of use
  • Business: Conversion, retention, support volume, onboarding completion
  • Engagement: DAU/MAU, session duration, feature discovery, return visits

HEART Framework

  • Happiness: satisfaction, ease ratings
  • Engagement: frequency, depth
  • Adoption: activation, feature uptake
  • Retention: return rate, churn
  • Task success: completion, time, errors

Metric Template

Name, definition, method, data source, target, frequency, owner.

Best Practices

  • Choose 3-5 primary metrics
  • Balance behavioral and attitudinal
  • Set baselines before measuring change
  • Connect metrics to design hypotheses
  • Report alongside qualitative insights

Frequently asked questions

What does the Metrics Definition AI skill do?

Define UX metrics and KPIs that connect design decisions to measurable outcomes. Use when choosing what to measure. For presenting the results afterwards, use `design-impact-reporting` (design-ops).

Why use Metrics Definition on TypingMind?

Because you install it once and use it with any model. Metrics Definition 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 Metrics Definition in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Owl-Listener/designer-skills/tree/main/ux-strategy/skills/metrics-definition. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Metrics Definition?

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 Metrics Definition?

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

Is the Metrics Definition AI skill free?

Yes. It is published on GitHub by Owl-Listener under the MIT 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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