figma-to-ai-prompter

Converts Figma design structures into token-optimized prompts for AI prototyping tools.

4|Updated May 16, 2026
One-click install
npx skills add https://github.com/reason-machines/design-skills --skill figma-to-ai-prompter-reason-machines
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: figma-to-ai-prompter
Source: https://github.com/reason-machines/design-skills/tree/main/skills/figma-to-ai-prompter
Command: npx skills add https://github.com/reason-machines/design-skills --skill figma-to-ai-prompter-reason-machines

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Manually translating Figma designs into prompts for AI prototyping tools produces bloated, imprecise prompts that waste tokens and generate inconsistent output. This Skill extracts design structure programmatically and generates compact, tool-specific prompts, reducing prompt size by up to 97%. ## Core Features & Use Cases - Design Structure Extraction: Pulls layouts, components, styles, and design tokens from Figma files via the Figma API. - Tool-Specific Prompt Templates: Generates targeted prompts for Lovable, Figma Make, Pencil.dev, Paper.design, and Google Stitch. - Token Optimization: Replaces frame attachments with structured MCP text context, cutting prompt size from 500+ tokens to roughly 45. - Use Case: A designer exports a Figma file, runs the transform script to extract the component hierarchy and style tokens, and receives a ready-to-paste Lovable prompt that produces a matching React app on the first generation. ## Quick Start Ask the AI to convert your Figma file into an optimized prompt for Lovable by providing the Figma file key and target tool.

Frequently Asked Questions about figma-to-ai-prompter

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert a Figma design into a prompt for Lovable?▼

Fetch the Figma file via the Figma API using your file key and personal access token, then run the transform script to extract the design structure. The extracted context is merged into the figma-to-lovable template, producing a prompt that specifies React, Tailwind, and the component hierarchy.

How do I reduce token usage when prompting AI tools with Figma designs?▼

Use structured MCP text context instead of frame attachments, which add 300-500 hidden tokens. Extract only essential properties like dimensions, colors, padding, and spacing, producing prompts around 45 tokens instead of 500 or more.

Which AI prototyping tools does Figma prompt generation support?▼

The workflow supports Lovable for full-stack React apps, Figma Make for interactive HTML prototypes, Pencil.dev for production React components, Paper.design for HTML/CSS canvas output, and Google Stitch for responsive UI generation.

Why does AI-generated code not match my Figma design?▼

Mismatch usually comes from vague prompts lacking explicit constraints. Add strict requirements for exact pixel values, hex colors, and spacing, then run an iterative validation loop comparing output against a published Figma Make URL to refine the prompt.

Can I extract design tokens and reusable components from Figma?▼

Yes, the extraction functions traverse the Figma node tree to collect colors, typography, spacing values, and COMPONENT or COMPONENT_SET nodes with their props and variants. These can be compiled into a design system prompt for component library generation.