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Plant Simulation Research Bridge

Plant Simulation Research Bridge

by AmaneSuzuha000
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

model_set_property

Set a writable attribute on a Plant Simulation model object and read it back to verify the change.

Instructions

Write one attribute declared writable for that object class, then read it back.

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": {
      "path": "<path>",
      "attribute": "<attribute>",
      "value": "<value>"
    },
    "name": "model_set_property"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
valueYes
work_dirNo
attributeYes
frame_pathNo
model_rootNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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 a write followed by a read-back and a writability precondition, but omits permissions, failure behavior, side effects, and what the read-back returns.

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 single sentence is front-loaded, efficient, and contains no wasted wording. Its terseness and the context-dependent phrase 'that object class' keep it from being fully self-contained.

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

Completeness2/5

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

For a six-parameter mutation tool with no annotations, no output schema, and no schema descriptions, the definition is not complete enough. It conveys the core write-and-verify operation but leaves most parameter meanings and error behavior unexplained.

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?

Schema description coverage is 0%, and the description only hints at the meanings of 'attribute' and 'value.' It leaves path, work_dir, frame_path, and model_root undocumented, so it does not compensate for the coverage gap.

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 verb and resource: write one writable attribute for an object class, then read it back. This clearly distinguishes setting from the sibling model_get_property, although it does not explicitly name that alternative.

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?

Usage is only implied by the phrase 'declared writable,' which tells the agent the attribute must be writable but gives no explicit when-to-use or when-not-to-use guidance. It does not mention alternatives such as model_get_property or object_set_control.

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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