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Plant Simulation Research Bridge

Plant Simulation Research Bridge

by AmaneSuzuha000
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

model_open

Load a .spp model into a running Plant Simulation instance and fingerprint the file for reproducible experiments and verification.

Instructions

Load a .spp model into the running Plant Simulation and fingerprint the file.

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>"
    },
    "name": "model_open"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
work_dirNo
model_rootNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full burden. It hints at an external dependency ('running Plant Simulation'), but never says whether loading replaces or conflicts with an existing model, what happens on failure, what 'fingerprint' means or returns, or whether the operation is idempotent. Key mutation semantics are left unstated.

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?

A single front-loaded sentence with no filler; the action and target come first. It is terse rather than padded, though that terseness is part of the transparency gap.

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?

No output schema and no annotations mean the description should explain the return of the fingerprint, prerequisites, and the roles of all three parameters. It does none of these, leaving an agent unable to predict the result of a load.

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 coverage is 0% across 3 parameters, so the description must compensate and largely does not: it implies 'path' points at a .spp file, but 'work_dir' and 'model_root' are never mentioned in either the schema or the description. Two of three parameters have no meaning attached anywhere.

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?

States a specific verb ('Load') and resource ('.spp model') plus a secondary action ('fingerprint the file'), which distinguishes it from the model_* siblings that manipulate objects inside an already-loaded model. The purpose is clear, though 'fingerprint' is left unexplained.

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 when-to-use guidance, no mention of prerequisites beyond the implicit 'running Plant Simulation', and no routing to alternatives such as model_status for checking load state. The agent must infer that this is the entry point before object-level model_* calls.

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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