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get_screenshot

Read-only

Export Figma nodes as PNG/JPG/SVG image blocks for the model, with auto-sizing and recovery of clipped or off-canvas nodes.

Instructions

Export nodes as images the model can see, one image block per node: { images: [{ nodeId, format, base64, width?, height?, scale?, recovered?, empty? }] }. format is PNG (default) / JPG / SVG. scale applies to raster formats; when omitted, each node is auto-fitted to a legible size (long edge into ~512–2576px: oversized frames scale down, tiny icons scale up ≤4x) — pass an explicit scale to force one. An explicit scale is capped so the long edge stays within 2576px, the most a vision model resolves: past that the model sees the identical pixels, so the extra bytes buy no detail — use save_screenshots when you need a full-res file on disk. Past 20 nodes in one call the whole batch drops to a 2000px long edge, which is what providers require of many-image requests; ask for fewer nodes when you need the detail. A batch is also capped by total size, not just resolution: a full-page frame is ~2.4MB, so 3–4 of them fill one response. Past that the remaining nodes come back labelled but not inlined, with a note naming them — re-request those ids in a follow-up call, or use save_screenshots for many nodes at once. Each raster label reports the exported width×height px and the scale, the anchor for mapping raster px back to design px. base64 is null for missing or non-exportable nodes. Nodes that are fully clipped or off-canvas (carousels, masks, off-screen states) are auto-recovered at their intrinsic bounds and flagged recovered:true. empty:true means the node genuinely renders nothing even unclipped (hidden / no content) so the export is blank.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scaleNoRaster scale factor (PNG/JPG); omit to auto-fit each node to a legible size
formatNoExport format: PNG (default) / JPG / SVG
nodeIdsYesFigma node ids to export
Behavior5/5

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

Annotations only declare readOnlyHint=true, but the description discloses extensive behavioral traits: auto-fit scaling behavior, scale caps at 2576px, batch size limits (20 nodes), total size caps (~2.4MB per frame), and handling of missing/recovered/empty nodes. This far exceeds what annotations provide and does not contradict them.

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?

Although lengthy, every sentence carries unique information about scaling, batching, edge cases, or alternatives. The description is front-loaded with the core purpose and output structure, then logically progresses through scale behavior, capacity limits, and recovery semantics without redundancy.

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

Completeness5/5

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

The description is remarkably complete: it specifies return format, scaling constraints, batch limitations, fallback behavior, and explicitly names alternatives. No output schema exists, so the description fully compensates by detailing the output shape and special flags, making the tool's behavior predictable in all mentioned scenarios.

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

Parameters5/5

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

Despite 100% schema description coverage, the description adds significant nuance: 'scale applies to raster formats; when omitted, each node is auto-fitted', 'explicit scale is capped so the long edge stays within 2576px', and format defaults. It also explains the meaning of output fields like base64, recovered, and empty, enriching understanding beyond the schema.

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 function: 'Export nodes as images the model can see' with a specific verb and resource. It also distinguishes itself from siblings by explicitly recommending 'save_screenshots' for full-res or batch needs, making the purpose unambiguous.

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?

The description provides explicit usage guidance: 'use save_screenshots when you need a full-res file on disk' and 'or use save_screenshots for many nodes at once.' It also gives conditions like 'ask for fewer nodes when you need the detail' and explains when batch limits apply, offering clear when-to-use vs. alternatives.

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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