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doodle

doodle

by 2648782102
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_board

Read-only

Reads shared canvas data—revision, object IDs, coordinates, authors, and BOARD_JSON—to answer questions about the drawing or give an AI agent visual context; read-only.

Instructions

读取人和 AI 共享画布的数据：revision、对象 ID、坐标、作者、BOARD_JSON 和画图规范。用于回答画布内容或给 Agent 提供视觉上下文；只读，不打开浏览器，也不写项目文件。想显示可编辑画布时调用 show_board。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_board"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior4/5

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

The annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description still adds real value beyond them by stating that it does not open a browser or write project files, and by listing the returned data fields. It does not describe pagination or size limits, which keeps it below a 5.

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?

Three short clauses with no filler: what data is returned first, then the use cases, then the exclusion and the sibling redirect. Nothing is repeated from the annotations and every sentence carries information.

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?

There is no output schema and no parameters, so the description carries the full burden of explaining the return shape. It discharges that by enumerating the returned fields and states the behavioral boundaries. An agent has everything needed to call it and interpret the result correctly.

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?

The tool takes zero parameters, so the baseline is 4; there is no input semantics to explain. The description instead spends its words on output content, which is the right allocation for a no-argument tool.

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 states a specific verb and resource (read the shared human/AI canvas data) and enumerates exactly what comes back: revision, object IDs, coordinates, author, BOARD_JSON and drawing specs. It explicitly contrasts with the sibling show_board, so an agent can distinguish the two without opening either schema.

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?

It gives two concrete positive use cases (answering questions about canvas content, supplying visual context to an Agent) and names the alternative plus the condition for it: call show_board when an editable canvas needs to be displayed. It also excludes behaviors (no browser opening, no project file writes), leaving little to infer.

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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