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andrewbartels1

SolidworksMCP-python

auto_dimension_view

Automates dimensioning of drawing views by analyzing geometry and adding overall sizes, hole diameters, radii, and critical features to accelerate drawing completion.

Instructions

Automatically dimension a drawing view.

Analyzes drawing view geometry and automatically adds common dimensions including overall sizes, hole diameters, radii, and critical features. Accelerates drawing completion and ensures comprehensive dimensioning coverage.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
input_dataYesThe input data value.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It states the tool adds dimensions automatically but lacks details on safety (non-destructive?), potential over-dimensioning, or side effects. The behavioral impact is only vaguely described.

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 concise with two sentences. The first sentence front-loads the main purpose, and the second adds detail. No unnecessary words or repetition.

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 that there is an output schema (mentioned in context), the description need not explain return values. However, it does not mention prerequisites (e.g., active drawing view) or what exactly 'input_data' should be. The tool is complex, so more context about the input and output would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'input_data' is an untyped object with no specific properties defined. The description does not clarify what this input should contain (e.g., view reference, options). The schema description is vague ('The input data value.'), and the tool description adds no further meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool automatically dimensions a drawing view by analyzing geometry and adding common dimensions. It mentions specific dimension types (overall sizes, hole diameters, radii). However, it does not explicitly differentiate from similar sibling tools like 'add_dimension', which is for manual dimensioning.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool vs alternatives, such as manual dimensioning or other automatic dimensioning tools. There is no mention of prerequisites, limitations, or best practices.

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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