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SolidworksMCP-python

SolidworksMCP-python

by andrewbartels1
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

set_dimension

Update a named dimension's value in the current SolidWorks model and automatically rebuild the design to reflect parametric changes.

Instructions

Set the value of a dimension in the current model.

This tool modifies the value of a named dimension and rebuilds the model. Use this to parametrically modify your model dimensions.

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": {
      "input_data": "<input_data>"
    },
    "name": "set_dimension"
  }
}

Input Schema

NameRequiredDescriptionDefault
input_dataYesThe input data value.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

The description mentions that the tool rebuilds the model, which is a behavioral consequence. Without annotations, it lacks details on prerequisites (e.g., model must be open) or side effects.

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 two sentences, concise and front-loaded with the core purpose. No extraneous information.

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's simplicity and presence of output schema, the description is mostly complete. It lacks failure conditions or mention that a model must be active.

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 coverage is 100%, so description adds no additional meaning beyond the schema. Baseline score of 3 is appropriate.

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 action ('Set the value'), resource ('a dimension'), and context ('in the current model'). It differentiates from siblings like 'get_dimension' (read) and 'add_dimension' (add new).

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 explicitly recommends use for parametric modification. However, it does not state when not to use this tool or mention alternatives like 'add_dimension'.

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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