Design System Interview logo

Design System Interview

Organization
KyaniteLabs
design-system-interview

Design-system interview before new frontend builds or redesigns. Use for vague site/app/landing/dashboard requests, generic-looking UI, direction-setting, aesthetic choices, type/color/density decisions, and DESIGN-SYSTEM.md tokens.

Overview

PublisherKyaniteLabs
Repositorytastecheck
Skill namedesign-system-interview
Stars
10
Forks
7
Bundled files
8
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.

  • 8 bundled files

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

  • Open source

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

Installation

Install the Design System Interview 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/KyaniteLabs/tastecheck/tree/main/skills/design-system-interview
  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/KyaniteLabs/tastecheck.git /tmp/tastecheck
mkdir -p .claude/skills
cp -r /tmp/tastecheck/skills/design-system-interview .claude/skills/design-system-interview
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Design System Interview 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 Design System Interview 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 Design System Interview 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.

Design System Interview

Turn a vague frontend brief into buildable decisions: study evidence, recommend a point of view, and ask only questions that materially change the build.

Start with direction, not questionnaire

Inspect product job, audience, content, marks, constraints, locales, and visual references before asking. Open with:

markdown
What I see: <the strongest signal in the brief>
My recommendation: <a specific direction>
Why it fits: <the product consequence>
Choose: <fork A and trade-off> / <fork B and trade-off> / redirect me

Ask one high-consequence fork at a time; combine only when one answer settles several decisions. Reflect each answer in one line for correction without rereading.

Interview loop

  1. Read the room. Separate current evidence from residue. If an existing direction covers five dimensions, confirm it and ask only for gaps.
  2. Propose a fork. Give two brief-compatible outcomes that look or behave materially differently. Recommend one and name its trade-off.
  3. Turn language into consequences. Translate “clean,” “premium,” or “bold” into hierarchy, density, material, type, color, or rhythm; do not debate adjectives.
  4. Record the decision. Mark committed, assumption awaiting confirmation, or blocked by contradiction, with supporting evidence.
  5. Stop when buildable. All nine dimensions are decided, delegated, or blocked; then write artifact and handoff.

Use 4–10 exchanges for a full interview. For urgent internal work, offer a short approval pass. In a one-shot/interrupted run, save the decision snapshot and first resume question; assumptions are not approval.

Decisions

Use adaptively; references/interview-contract.generated.md is canonical session/dimension authority. Examples teach format, never taste.

Canonical IDClose with
referencea real artifact and what it earns
personalitya chosen pole, not a middle
aestheticone concrete phrase predicting hierarchy/material
typebinding evidence, display/body stance, language/measure risk
color_modedominant hue, accent job, and light/dark commitment
density_shapedensity, numeric radius range, elevation
structure_rhythmcomposition, motif, and sectional cadence
signatureone memorable move
imagery_iconographysource/treatment or absence; one icon system

Optionally set motion level.

User receives

Write DESIGN-SYSTEM.md from assets/DESIGN-SYSTEM.template.md, then give an approvable build handoff:

  1. Direction: sentence predicting the interface.
  2. Decisions: completed decision map.
  3. Refusals: three to five defaults this product will not use.
  4. Build contract: semantic tokens, structural rhythm, responsive/accessibility constraints.
  5. Next move: first implementation step, or exact blocker and owner.

Read references/session-protocol.md for readiness/resume rules.

markdown
| Dimension / conflict | Evidence | Decision or assumption | Consequence | Confirmation / owner |
| --- | --- | --- | --- | --- |
| Alert hierarchy | ... | committed / assumed / blocked | ... | ... |

Use approved only when confirmed and buildable. Use approval-ready when recommendations and tokens await confirmation; do not hand it to implementation. Use blocked when contradiction or missing authority prevents a safe recommendation. Cite non-obvious choices; each token needs a real build job.

The committed direction in one line: "<source-derived aesthetic phrase> — <chosen
hierarchy>, <color role>, <type stance>, <shape/density>, signature = <specific move>."

Hand hue to color-system, type to web-typography, modes to theming, tokens to implementation skills, and the spec to deslop-ui. Keep one DESIGN-SYSTEM.md source of truth.

Reference files

  • references/interview-bank.md — forks and abstention.
  • references/structure-and-rhythm.md — composition/rhythm.
  • references/tokens.md — token architecture.
  • references/decision-records.md — novel cases.
  • references/session-protocol.md — shortcut, contradiction, resume.
  • references/interview-contract.generated.md — generated authority.

Ready-to-build check

Report rows with direct evidence, reason, remediation, and pass/fail/n/a.

CheckStatusEvidence / provenanceReasonRemediation
Nine required dimensions decided
Existing-direction shortcut or full interview justified
Contradictions and trust-critical rationale resolved
DESIGN-SYSTEM.md and canonical token block complete
Downstream handoff is explicit

Build-ready requires every row passing and artifact approved. approval-ready or blocked is a resumable checkpoint: name unresolved owner and next confirmation; do not start implementation. Deliver one-line direction, link artifact, then state next action.

Contract (generated)

Canonical detail: contract.json.

  • Route: A new interface or redesign lacks a committed visual direction (+1 in contract.json); avoid: An existing site has sufficient evidence to improve without a new direction interview (+1 in contract.json)
  • Exclude: Do not begin implementation before direction is resolved or explicitly assumed (+1 in contract.json)
  • Stop / handoff: Pause when contradictory or trust-critical direction is unresolved (+1 in contract.json); receives [none] -> sends [art-direction, color-system, component-states, data-viz, deslop-ui, empty-states, form-ux, humanize-copy, micro-motion, responsive-layout, spacing-system, tasteroll, theming, web-typography]
  • Output: A decision-complete design-system artifact with explicit assumptions and readiness state
  • Evidence: table_with_evidence with status, reason, remediation, evidence, provenance.

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 Design System Interview AI skill do?

Design-system interview before new frontend builds or redesigns. Use for vague site/app/landing/dashboard requests, generic-looking UI, direction-setting, aesthetic choices, type/color/density decisions, and DESIGN-SYSTEM.md tokens.

Why use Design System Interview on TypingMind?

Because you install it once and use it with any model. Design System Interview 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 Design System Interview in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/KyaniteLabs/tastecheck/tree/main/skills/design-system-interview. 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 Design System Interview?

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 Design System Interview?

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

Is the Design System Interview AI skill free?

Yes. It is published on GitHub by KyaniteLabs 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇