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Figma CodeKit — Pixel-Verified Figma to Code

Figma CodeKit — Pixel-Verified Figma to Code

Inspect the design structure

figma_inspect

Print the converted design’s IR tree as an indented outline to understand its structure and find specific elements without reading raw Figma JSON or the full ir.json.

Instructions

Print the IR tree as an indented outline (role, name, box, layout, text, tokens) so you can understand the design structure and find a specific element without reading raw Figma JSON or the whole ir.json. Use after figma_convert.

Input Schema

NameRequiredDescriptionDefault
dirYesCache dir from figma_convert.
depthNoMax tree depth to print.
filterNoOnly show nodes whose name or text matches this (case-insensitive substring).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden alone; it does disclose that the operation prints an outline rather than mutating anything and describes the shape of that output. It is silent on side effects, output size/pagination for large trees, and failure behavior when dir is invalid or absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the action and its output format, followed by a short rationale-and-ordering sentence. There is some redundancy between "understand the design structure" and the enumerated fields, but nothing is wasted at length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A simple three-parameter read tool with no output schema, and the description explains what the returned outline contains and what fields it shows. That is nearly everything an agent needs, with only edge-case behavior (empty results, invalid dir) left unspecified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so dir, depth, and filter are already documented in the schema. The description adds no extra parameter meaning such as how filter interacts with depth or the default depth of 4, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Print the IR tree as an indented outline") and even enumerates the fields emitted (role, name, box, layout, text, tokens). This clearly separates it from figma_convert and figma_verify, which produce/check the IR rather than read it back.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit sequencing ("Use after figma_convert") and the motivating job ("find a specific element without reading raw Figma JSON or the whole ir.json"). It does not contrast with figma_verify or say when inspection is unnecessary, so it stops short of full when/when-not guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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