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Plant Simulation Research Bridge

Plant Simulation Research Bridge

simulation_reset

Resets the EventController while leaving the model unchanged, enabling experiments to restart from a clean event state without reloading or altering the model.

Instructions

Reset the EventController without touching the model.

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": "simulation_reset"
  }
}

Input Schema

NameRequiredDescriptionDefault
work_dirNo
model_rootNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are supplied, so the description carries the full behavioral burden. It discloses one useful trait (the model is left intact) but says nothing about what internal state is discarded on reset, whether it is reversible, whether it requires a running simulation, or how errors are surfaced - all critical for a state-mutating operation.

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 well-formed sentence with no padding and the scope qualifier placed where it matters. It is efficient, though its brevity reflects under-specification rather than disciplined editing.

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

Completeness1/5

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

For a mutating tool with no annotations, no output schema, and two entirely undocumented parameters, one short sentence is far too little. The agent lacks the prerequisites, side effects, and parameter meaning needed to invoke this confidently.

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?

Two parameters (work_dir, model_root) at 0% schema description coverage, and the description mentions neither. An agent cannot tell whether these default to a session context or must be supplied, nor how they interact with an EventController that is being reset.

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

Purpose3/5

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

States a specific verb ("Reset") and a specific resource ("EventController"), and adds a scope qualifier ("without touching the model") that separates it from the model_* siblings. However, "EventController" is unexplained domain jargon and nothing clarifies how a reset differs from simulation_stop, so the agent must guess at the actual effect.

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?

Provides no when-to-use guidance: no prerequisites (must a run be active?), no exclusions, and no named alternative among simulation_stop/simulation_start/simulation_status. The only implicit guidance is the negative scope clause, which tells the agent what is NOT affected rather than when to pick this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.