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import_image

Destructive

Import base64-encoded PNG or JPG images into Figma as rectangle nodes with specified dimensions, positioning, and scale modes.

Instructions

Import a base64-encoded image into Figma as a rectangle with an image fill. Use get_screenshot to capture images or provide your own base64 PNG/JPG.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
heightNoHeight in pixels (default 200)
imageDataYesBase64-encoded image data (PNG or JPG)
nameNoNode name
parentIdNoParent node ID in colon format. Defaults to current page.
scaleModeNoImage scale mode: FILL (default), FIT, CROP, or TILE
widthNoWidth in pixels (default 200)
xNoX position (default 0)
yNoY position (default 0)
Behavior4/5

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

Annotations declare write/destructive/non-idempotent hints. Description adds valuable behavioral context beyond annotations: it specifies the node creation pattern (rectangle with image fill) and input constraints (PNG/JPG formats). It does not explicitly describe the non-idempotent nature (calling twice creates two nodes) but covers the creation side-effect well.

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

Conciseness5/5

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

Two sentences with zero waste. First sentence front-loads core functionality and mechanism; second sentence provides practical workflow guidance. Every word earns its place.

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?

Given 8 parameters with full schema coverage and annotations present, the description adequately covers the creation behavior and input sourcing. Minor gap: no output schema exists, and description doesn't mention what gets returned (e.g., node ID/object), though this is somewhat implied by the creation context.

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

Parameters4/5

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

Schema has 100% coverage, establishing baseline 3. Description adds format constraints (PNG/JPG) not explicitly stated in the schema's 'base64-encoded image data' description, and provides workflow context for sourcing imageData via get_screenshot. It elevates the parameter understanding beyond the schema alone.

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?

Description provides specific verb (Import), resource (base64-encoded image), target (Figma), and structural outcome (rectangle with image fill). It clearly distinguishes from siblings like create_rectangle (empty shape) and get_screenshot (capture only).

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?

Explicitly references sibling tool get_screenshot as a workflow source for imageData ('Use get_screenshot to capture images'), establishing a clear tool pairing. Lacks explicit 'when-not-to-use' guidance against alternatives like direct file imports, but provides strong contextual workflow.

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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