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dev48v

Excalidraw MCP Diagram Agent

by dev48v

Create an Excalidraw diagram

create_diagram

Describe a system in plain English to generate an editable Excalidraw scene with auto-layout, bound arrows, and attached labels. Optionally save to .excalidraw file.

Instructions

Describe a system in plain English and get back a complete, editable Excalidraw scene: shapes laid out automatically, arrows genuinely bound to the shapes they connect, and labels attached to their containers. Optionally writes the scene to a .excalidraw file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNoOptional title drawn above the diagram.
directionNoFlow direction: 'right' (default) or 'down'.right
save_pathNoOptional absolute path to write the .excalidraw file to.
use_modelNo'auto' uses the configured model and falls back to the offline rule parser, 'never' forces the offline parser, 'always' fails if no model is reachable.auto
descriptionYesWhat to draw, e.g. 'A React app calls an API that reads Postgres and publishes to Kafka'. Arrow syntax like 'A -> B: label' also works.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: shapes laid out automatically, arrows bound to shapes, labels attached to containers, and optional file writing. However, it omits potential side effects such as file overwrite behavior if save_path exists, and does not mention failure modes.

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?

The description is three sentences, front-loaded with the core function. Each sentence earns its place: main action, output quality details, and optional file write. No wasted words.

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 the tool has 5 parameters and an output schema, the description gives a solid high-level understanding of the output (editable scene with bound arrows) and optional file write. It does not explain error conditions or model-specific usage, but the schema covers parameter details and the output schema likely covers return values.

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 baseline is 3. The description adds minimal parameter context by mentioning optional file writing (save_path), but does not elaborate on direction, title, or use_model beyond what the schema already provides.

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 opens with 'Describe a system in plain English and get back a complete, editable Excalidraw scene' – a specific verb (get back) and resource (Excalidraw scene). It clearly distinguishes the creation function from sibling tools like validate_diagram and diagram_backend_status.

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?

The description clearly implies when to use the tool: when you need a diagram from a plain-English description. It sets context with details about layout and optional file writing, but does not explicitly mention when not to use it or reference alternatives like validate_diagram, so it lacks explicit exclusions.

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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