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alucardeht

Figma MCP

by alucardeht

get_frame_info

Analyze Figma frame structure to identify components, text, colors, and styles before implementation or screenshot capture.

Instructions

Get detailed info about a specific frame.

IMPORTANT: This should be your FIRST call for any implementation task. Always call get_frame_info BEFORE taking screenshots to understand the structure.

HOW IT WORKS:

  • Returns all components, text, colors, and styles

  • Large frames (>1000 elements) trigger warning with strategy

  • Use depth parameter to control detail level

  • Automatically chunks if response too large

The tree includes special markers:

  • isCompositeAsset: true = Export this GROUP as a single image (contains image + shapes)

  • isSmallElement: true = Small UI element that may be easily missed

TYPICAL WORKFLOW:

  1. list_frames → find frame name

  2. get_frame_info(frame_name) → structure

  3. extract_styles → design tokens

  4. extract_assets → icons/images

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_keyYesFigma file key
page_nameYesPage name (partial match)
frame_nameYesFrame name (partial match)
depthNoHow deep to traverse (1=direct children, 2=grandchildren). Default: 2
continueNoContinue from last response
Behavior4/5

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

With no annotations, the description carries full burden and provides substantial behavioral context: it describes return content (components, text, colors, styles), handling of large frames (warning with strategy), chunking behavior, and special markers (isCompositeAsset, isSmallElement). It doesn't mention rate limits or authentication needs, but covers most operational behaviors well.

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?

Well-structured with clear sections (IMPORTANT, HOW IT WORKS, TYPICAL WORKFLOW) and front-loaded key information. Some sentences could be more concise (e.g., the workflow section is somewhat redundant with earlier guidance), but overall it's efficiently organized with minimal waste.

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?

For a tool with 5 parameters, no annotations, and no output schema, the description provides good contextual coverage: purpose, sequencing, behavioral traits, and workflow integration. It doesn't fully describe the return format or error conditions, but given the complexity and lack of structured fields, it's reasonably complete for agent use.

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 the schema already documents all 5 parameters. The description adds some context about the depth parameter ('control detail level') and implies frame_name comes from list_frames, but doesn't provide additional syntax or format details beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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?

The description clearly states the tool's purpose with specific verbs ('Get detailed info') and resource ('about a specific frame'). It distinguishes from siblings by focusing on frame-level details rather than page analysis (analyze_page_structure), asset extraction (extract_assets), or listing (list_frames). The opening sentence directly answers 'what does this tool do?'

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

Usage Guidelines5/5

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

Explicit guidance is provided: 'This should be your FIRST call for any implementation task' and 'Always call get_frame_info BEFORE taking screenshots'. The TYPICAL WORKFLOW section shows sequencing with list_frames and other tools. Clear when-to-use context is established, though alternatives aren't explicitly named.

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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