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KiCad MCP Server

KiCad MCP Server

by brovk2008
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

list_dimensions

Retrieve dimension annotations from a PCB layout, with optional filtering by layer name.

Instructions

List dimension annotations on the board, optionally filtered by layer name.

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": "list_dimensions"
  }
}

Input Schema

NameRequiredDescriptionDefault
layer_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral transparency. It does not disclose whether the operation is read-only, what the output format is, or if any side effects occur. The minimal description ('list...') fails to convey essential behavioral traits beyond the basic action.

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 a single sentence with no extraneous information. It efficiently conveys the core function and filtering capability, demonstrating conciseness without sacrificing necessary content.

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

Completeness3/5

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

Given the low complexity (one optional parameter, no output schema), the description is minimally adequate but lacks important context such as what the list returns (full dimension objects or summaries), pagination behavior, or any ordering. The absence of output schema means the agent lacks guidance on return structure.

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 schema has 0% description coverage for the only parameter 'layer_name'. The description adds value by explaining that this parameter filters results by layer name, which clarifies its purpose beyond the schema's type and default. More detail (e.g., valid layer name values) could improve, but it is adequate.

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 lists dimension annotations on the board, with optional filtering by layer name. The verb 'list' and resource 'dimension annotations' are specific, and it distinguishes from sibling 'get_dimension' (which retrieves a single dimension) and other list_* tools for different entities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for viewing dimensions but does not explicitly state when to use this tool versus alternatives like 'get_dimension' or other list tools. No when-not-to-use or prerequisite information is provided, leaving the agent to infer context from sibling names.

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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