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describe_scene

Summarize an Excalidraw scene as structured element data—counts, bounds, positions, sizes, text, and bindings—so agents can plan edits without parsing pixels.

Instructions

What is on a scene, as structure rather than pixels: counts by type, overall bounds, and a rounded summary of each element with its id, position, size, text and bindings. Cheaper than read_scene and usually enough to plan an edit.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "scene": "<scene>"
    },
    "name": "describe_scene"
  }
}

Input Schema

Name	Required	Description
`type`	No	Only elements of this type.
`limit`	No	Max elements to list (default 400).
`scene`	Yes	Scene id, exact name, or a unique part of the name. Use list_scenes if unsure.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.2Oct 18, 2026

TDQS

A4.2/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full burden, and it does disclose the return shape: counts by type, bounds, and per-element id/position/size/text/bindings. It does not mention read-only guarantees, permissions, or output limits/pagination behavior.

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, front-loaded with what the tool returns and followed by the cost/alternative rationale. Every clause earns its place with no redundancy.

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 read tool with no annotations and no output schema, the description compensates well by enumerating the returned fields and cost tradeoff. It is nearly complete, missing only explicit read-only confirmation and any note on result size limits beyond the schema's limit default.

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 all three parameters (type filter, limit default 400, scene identifier) are already documented in the schema. The description adds no format or semantic detail beyond what the schema provides, matching the baseline for full coverage.

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 (describe) and resource (scene) and immediately qualifies the output as structural rather than pixel data. It is clearly distinguishable from siblings like read_scene and render_scene.

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 routes against the closest alternative: 'Cheaper than read_scene and usually enough to plan an edit' tells the agent when this is preferable. It stops short of stating when read_scene is required instead, so there is no explicit exclusion condition.

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