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Token Mapping

Community
arla6ka
token-mapping

Use to report how hardcoded style values on a page, file or diff map onto a project's existing design tokens, such as "are we using our tokens here", "which hardcoded colors map to which tokens", a token audit or planning a token migration. It never edits. Replacing the values is build-design-system.

Overview

Publisherarla6ka
Repositorydesign.how
Skill nametoken-mapping
Stars
200
Forks
15
Bundled files
1
LicenseMIT
Links
  • 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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by arla6ka on GitHub. Read the source before you install it.

Installation

Install the Token Mapping 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/arla6ka/design.how/tree/main/skills/token-mapping
  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/arla6ka/design.how.git /tmp/design.how
mkdir -p .claude/skills
cp -r /tmp/design.how/skills/token-mapping .claude/skills/token-mapping
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Token Mapping 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 Token Mapping 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 Token Mapping 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.

Token mapping

A read-only report that lands raw values (hex, px, shadows) on a token list someone else owns. Classes, normalising and tolerances are in references/mapping-rules.md. "Check the tokens on the settings page" is enough of an ask. Find the values and the list yourself.

Steps

  1. Find the list. Token files, theme entries, custom properties on :root, a component library's variable pairs. A framework's default theme is not the team's list, and neither is a public system's (Geist's names never stand in for the team's). Record its name, location and how you read it. If a read fails, say so and stop. Never fill a list from memory.
  2. Find the values. What the person named, else the branch diff, else the product code. Record each with its file, line, property and job.
  3. Resolve. Follow every alias to its final value in each mode. Write down every disagreement between two sources.
  4. Normalise both sides (lengths to px, colours to OKLCH compared by delta E OK) with code, never by eye.
  5. Classify each row once per mode. Purpose first, then value.
    • Exact: the token's stated job covers the row and the values match.
    • Semantic: the job covers it and the value is inside tolerance. State the difference in numbers.
    • Ambiguous: two or more tokens fit and nothing picks one. Name every candidate.
    • Gap: no token's job covers it, or the only fitting token is out of tolerance. A gap never gets a new name.
  6. Count and close. When gaps are over 30% of rows and number 12 or more, the list is usually the wrong one. Say so, still deliver the table, and lead with Status: not actionable (gap threshold).

Report

Summary, Mapping, Do not use (a token whose value matches but whose job differs), Ambiguous, Gaps, For a person to decide, Source. Last line Coverage: with what was scanned and what was not. Run on its own, the chat reply gives the answer with its numbers and one prompt the person can paste to take the next step.

Rules

  • A match on value before purpose is wrong. Wrong: #6b7280 mapped to color.border.default because the hex is equal. Right: it is text, so the candidates are text tokens, and the border token goes in Do not use.
  • A semantic token wins over the primitive it aliases. Map to a primitive only when no semantic token covers the job, and say so.
  • A palette class (text-gray-500) names a value and no job. It gets a row, counted apart from raw values.
  • Anything inferred rather than read, such as a job taken from a class name, is marked inferred.
  • Counts carry their unit: occurrences, lines or mapping rows.

Stops

Stop and report on these only. No list exists. One name has two values in the same mode. Two sources disagree and no project rule says which wins (report both). Return what stopped it, the groundwork so far, and the shortest message that unblocks it, such as "Paste tokens.json or give its path."

Done

Every row has a job, a class and a reason. Every ambiguous row names two or more candidates. Nothing in the repo changed (git status is the same before and after). The last line reads Coverage:.

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 Token Mapping AI skill do?

Use to report how hardcoded style values on a page, file or diff map onto a project's existing design tokens, such as "are we using our tokens here", "which hardcoded colors map to which tokens", a token audit or planning a token migration. It never edits. Replacing the values is build-design-system.

Why use Token Mapping on TypingMind?

Because you install it once and use it with any model. Token Mapping 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 Token Mapping in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/arla6ka/design.how/tree/main/skills/token-mapping. 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 Token Mapping?

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 Token Mapping?

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

Is the Token Mapping AI skill free?

Yes. It is published on GitHub by arla6ka 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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