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CST-MCP

CST-MCP

by woson-L
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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cst_model_audit_tool

Audit a built CST model to verify solids, materials, volumes, and bounding boxes, catching geometry or material issues before simulation.

Instructions

Audit the built model: solids, materials, volumes and bounding boxes.

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": "cst_model_audit_tool"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses little. It does not say the operation is read-only, that it requires an open/built project, or whether it is expensive or has side effects. It only lists the categories inspected.

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?

A single sentence with the verb and the inspected categories front-loaded, and no wasted words.

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?

An output schema exists, so return values need not be explained in the description. For a zero-parameter read tool this is close to sufficient, with the only real gap being prerequisites and the read-only nature that annotations would otherwise supply.

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 there is no parameter semantics to document; per the rubric this is the baseline 4. The description appropriately adds no parameter detail.

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 names a specific verb (audit) and resource (the built model) and enumerates what is inspected: solids, materials, volumes, bounding boxes. That is far more informative than a tautology, though it does not explicitly contrast itself with siblings like cst_project_info_tool or cst_health_check_tool.

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?

There is no indication of when to reach for this tool versus the many other inspection/reporting siblings (cst_project_info_tool, cst_health_check_tool, cst_list_results_tool). No prerequisites (e.g. project must be open and a model built) are stated.

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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