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    Figma AI-Readiness Audit

    1

    Scores a Figma frame on how well AI can turn it into code: layer naming, auto-layout, variables and tokens, and component structure. Returns a 20-point report with concrete fixes to make in Figma.

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    Figma AI-Readiness Audit

    Figma AI-Readiness Audit

    Example session with this skill installed

    /figma-audit https://www.figma.com/design/<fileKey>/tidy-up-claude?node-id=0-49

    • Read your context and instructions
    • Compiled the figma ai-readiness audit
    • Generated the app files

    Figma AI-Readiness Audit Report

    File: tidy-up-claude
    Target node: backup (0:49) — HILMA, a Scandinavian interior e-commerce home page (1440 × 3598)

    Overall score: 15 / 20

    DimensionScoreRating
    A. Layer naming3 / 5🟡 Room for improvement
    B. Auto-layout4 / 5🟢 Good
    C. Variables & tokens4 / 5🟢 Good
    D. Component structure4 / 5🟢 Good

    Strengths

    • Every color and spacing value in the generated code resolves to a variable (var(--brand/primary), var(--space/80)), with no stray hex values.
    • 13 text styles are defined and applied (H1/Light, Body, Display/Price, and so on), so AI can map typography to a real type scale.
    • Header, Footer, Product Card and Button are real components used as instances. Button variants are named on a Size × State axis (Default / Hover / Disabled).
    • Sections carry semantic names (hero, featured-products, brand-story, newsletter) that translate directly into component names.

    Improvement suggestions

    Root frame backup (0:49)
    • Problem: The top-level frame is named backup, which says nothing about the page.
    • Impact: AI uses the root name for the page component, so it generates export default function Backup().
    • Suggestion: Rename it to the page's role, for example HomePage or Top.
    Text node Read Our Story (0:90)
    • Problem: The layer name is the raw text content, while every other text node has a role-based name.

    Impact: If the copy changes, the layer name no longer describes the element. It also breaks the naming pattern AI relies on.

    • Suggestion: Rename it to story-cta-label.
    Four sibling divider-wrapper frames (10:2, 10:3, 0:94, 10:4)

    Problem: Four identical wrapper frames with height 0 sit between sections, all with the same name. Each one wraps a single line.

    • Impact: AI emits four h-0 wrapper divs with the divider exported as an image, instead of a border or an <hr>.
    • Suggestion: Drop the wrappers and use a top stroke on each section, or make one Divider component.
    space/17 spacing token (newsletter input and Button)
    • Problem: The 17px padding is tokenized, but it is off the 4/8px grid used everywhere else.
    • Impact: AI can't map it to a standard spacing scale and ends up writing an arbitrary value like py-[17px].
    • Suggestion: Use space/16 and let the fixed 52px height handle the vertical alignment.
    Product Card instance sizing (14:3 vs 14:8 / 14:13)
    • Problem: The first card uses Fill container, but the other two are fixed at 405.333px.

    Impact: AI generates flex-1 for one card and w-[405.333px] for the other two, so the grid won't reflow at other widths.

    • Suggestion: Set all three instances to Fill container.

    Summary

    This frame is already in good shape for AI. Variables, text styles and components are all in place. Fixing the root name and the Product Card sizing would remove the two things most likely to produce visibly wrong code.

    figma-ai-readiness-audit-app.zip

    ZIP · project files

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    AI design-to-code output is only as good as the Figma file it reads. A frame full of "Frame 123" layers, manually positioned children, hardcoded hex values and copy-pasted cards produces code with the same problems: meaningless component names, absolute positioning, arbitrary values and duplicated markup. This skill checks a frame for exactly those problems before anyone starts implementing it.

    What it does

    • Scores the frame 0–5 on each of 4 dimensions (20 points total): layer naming, auto-layout usage, variables and tokens, and component and instance structure
    • Flags auto-generated layer names, duplicate sibling names, generic names and text layers named after their own content
    • Finds manually positioned children, empty spacer frames used in place of gap settings, and fixed spacing values with no tokens behind them
    • Checks whether colors and spacing are bound to variables and whether text styles are defined and applied, based on the code Figma actually generates
    • Spots repeated structures that were never made into components, and state variations built as separate frames instead of variants
    • Lists what the file already does well, so the report isn't only a list of problems

    How it works

    1. Takes a Figma frame URL
    2. Fetches the frame's generated code, screenshot and style information, along with its layer hierarchy, through the official Figma MCP server
    3. Checks the frame against a fixed checklist for each dimension
    4. Returns a scored report. For each issue, it names the exact layer, explains how it would hurt the generated code, and gives a specific fix to make in Figma.

    What it is not

    This is a read-only report. It never edits the Figma file and does not write any code. It tells you what to fix, and you make the changes in Figma, or with a separate cleanup skill if you have one.

    Requirements

    Runs inside an agent connected to the official Figma MCP server, the same connection used for Figma-to-code work. It uses only get_design_context and get_metadata. No local file access and no other network calls.

    More from KMRVID

    The full Claude Code skill bundle for Figma, Tailwind and Astro workflows is available on Gumroad: https://gaspanik.gumroad.com/l/kmrvid-claudeskills

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
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      Download the ZIP

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      Unzip into your skills folder

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      Ask your agent to use it

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