Metrics Basics

Community

nemanli

metrics-basics

Defines UX measurement frameworks, terms, and philosophy when the user is learning the foundation rather than applying it — "what is HEART?", "define cohort retention", "what is MDE?", "what's a decision rule?", "why do we measure things this way?". Skip when a real situation is in mind (redesign, metric drop, stakeholder report, pre-launch plan, A/B test, tracking plan, claim review) — those go to the content skills.

Overview

Publisher	nemanli
Repository	`ux-metrics-skills`
Skill name	`metrics-basics`
Stars	3
Forks	0
Bundled files	4
License	MIT
Links	Skill source Repository

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 nemanli on GitHub. Read the source before you install it.

Installation

Install the Metrics Basics 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/nemanli/ux-metrics-skills/tree/main/skills/metrics-basics
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.

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/nemanli/ux-metrics-skills.git /tmp/ux-metrics-skills
mkdir -p .claude/skills
cp -r /tmp/ux-metrics-skills/skills/metrics-basics .claude/skills/metrics-basics

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

Use it in TypingMind

Enable Metrics Basics 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 Basics 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 Basics 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.

Overview

Shared foundation for every metrics skill in this repo. Holds the HEART framework, measurement philosophy, the term glossary, and the 4 context anchors used by adaptive mode. Other skills (metrics-ux, metrics-spec, metrics-instrumentation, metrics-diagnose, metrics-review, metrics-present) read these references when they need shared context.

When to Use

Use this skill when:

The user asks directly about HEART (categories, Goals–Signals–Metrics, choosing categories).
The user asks what a metric term means (e.g. "what's a baseline?", "what's a cohort?").
The user asks a meta question about measurement ("why measure this?", "when should we not measure?").
Another skill needs the 4 context anchors to run its adaptive questionnaire.

Do not use this skill when the user has a concrete task that fits a content skill (UX measurement, diagnosing a metric drop, presenting results). Those skills load this one's references as needed.

References

Read only what the current task requires. Do not load all references by default.

heart.md — Google HEART framework: 5 categories, Goals–Signals–Metrics, choosing categories, baselines, common pitfalls. Read when the user mentions HEART, picks UX categories, or needs the Goals–Signals–Metrics process.
measurement-philosophy.md — why we measure, what measurement is not, when not to measure. Read when the user questions the value of measurement, proposes a vanity metric, or asks meta questions.
glossary.md — definitions of recurring terms (baseline, cohort, vanity metric, Goodhart, counter-metric, HEART, NPS, MDE, decision rule, tracking plan, PII, SRM, etc.) grouped by category: frameworks, UX metrics, statistics, communication, and planning/experimentation/instrumentation/review. Read when the user asks what a term means or uses one ambiguously.
context-questions.md — full wording of the 4 anchors (SCOPE / STAGE / AUDIENCE / DATA), present-vs-missing prompt examples, decision logic, and the inline-list convention for asking the user. Read when running the adaptive questionnaire in vague mode or when any skill is about to ask the user something.

Bundled files

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

references/context-questions.md11 KB
references/glossary.md18 KB
references/heart.md8 KB
references/measurement-philosophy.md17 KB

Frequently asked questions

What does the Metrics Basics AI skill do?

Why use Metrics Basics on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nemanli/ux-metrics-skills/tree/main/skills/metrics-basics. 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 Metrics Basics?

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 Basics?

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

Is the Metrics Basics AI skill free?

Yes. It is published on GitHub by nemanli 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Overview

When to Use

References

Bundled files

Frequently asked questions

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