The prompt
You are a design systems architect. I'm providing you with a raw design audit JSON from an existing codebase. Your job is to transform this chaos into a structured token architecture.
## Input
[Paste the Phase 1 JSON output here, or reference the file]
## Token Hierarchy
Design a 3-tier token system:
### Tier 1 — Primitive Tokens (raw values)
Named, immutable values. No semantic meaning.
- Colors: `color-gray-100`, `color-blue-500`
- Spacing: `space-1` through `space-N`
- Font sizes: `font-size-xs` through `font-size-4xl`
- Radii: `radius-sm`, `radius-md`, `radius-lg`
### Tier 2 — Semantic Tokens (contextual meaning)
Map primitives to purpose. These change between themes.
- `color-text-primary` → `color-gray-900`
- `color-bg-surface` → `color-white`
- `color-border-default` → `color-gray-200`
- `spacing-section` → `space-16`
- `font-heading` → `font-size-2xl` + `font-weight-bold` + `line-height-tight`
### Tier 3 — Component Tokens (scoped to components)
- `button-padding-x` → `spacing-4`
- `button-bg-primary` → `color-brand-500`
- `card-radius` → `radius-lg`
- `input-border-color` → `color-border-default`
## Consolidation Rules
1. Merge values within 2px of each other (e.g., 14px and 15px → pick one, note which)
2. Establish a consistent spacing scale (4px base recommended, flag deviations)
3. Reduce color palette to ≤60 total tokens (flag what to deprecate)
4. Normalize font size scale to a logical progression
5. Create named animation presets from one-off values
## Output Format
Provide:
1. **Complete token map** in JSON — all three tiers with references
2. **Migration table** — current value → new token name → which files use it
3. **Deprecation list** — values to remove with suggested replacements
4. **Decision log** — every judgment call you made (why you merged X into Y, etc.)
For each decision, explain the trade-off. I may disagree with your consolidation
choices, so transparency matters more than confidence.
How to use this prompt
Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.
Which AI model works best
ChatGPT, Claude, and Gemini all produce useful results for this type of prompt. Claude is usually the most nuanced, ChatGPT the fastest, and Gemini the best when visual input or Google Workspace data is involved.
How to customize this prompt
Adapt the prompt to your specific use case. Replace placeholders (usually in brackets or caps) with your own context. The more detail you provide, the more precise the response.
Common use cases
- Use directly in ChatGPT, Claude, or Gemini
- Adapt to your specific project or industry
- Use as a starting point for your own custom prompt
- Compare across models to find the best fit for your case
- Share with your team as a standard workflow
Variations
Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).
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