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cad-mcp

cad-mcp

by Arookie127
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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describe_model

Retrieve full details of a built model—parameters, topology, bounding box, files—to recall the exact parameters used mid-session.

Instructions

Full information about a model you built: parameters, topology, bounding box, files.

Use it mid-session to recall which parameters this model was actually built from.

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": {
      "name": "<name>"
    },
    "name": "describe_model"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the kinds of information returned, but does not state that the operation is read-only, whether it has side effects, what happens if the model does not exist, or any permission requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with no wasted text, and it front-loads the returned information before the usage note. It could be slightly more structured, but it is efficient.

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?

With no output schema, the description must explain return values, and it does list major categories. It remains incomplete for the single required parameter and for error or not-found behavior, leaving some gaps for an agent invoking the tool.

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?

There is one required parameter, 'name', with 0% schema description coverage. The description implies the name identifies 'a model you built', but does not explain the expected format, uniqueness, or source of the name, so it fails to compensate for the missing parameter documentation.

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 states a specific retrieval action and enumerates what information is returned: parameters, topology, bounding box, and files. It is clearly a metadata lookup for a built model, though it does not explicitly name how it differs from siblings like list_parts or check_mesh.

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?

It gives a concrete usage occasion: mid-session, to recall the parameters a model was built from. However, it does not name alternatives or describe when not to use this tool, leaving routing guidance implicit.

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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