ltspice-mcp

run_montecarlo

Launch a preconfigured Monte Carlo circuit simulation asynchronously. Returns a job ID for immediate tracking, enabling efficient variation analysis without blocking your workflow.

Instructions

Execute a previously configured Monte Carlo analysis asynchronously and return a job_id immediately.

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": {
      "config_id": "<config_id>"
    },
    "name": "run_montecarlo"
  }
}

Input Schema

Name	Required	Description	Default
`config_id`	Yes	Configuration ID from configure_sweep or configure_montecarlo
`max_parallel`	No	Max concurrent simulations (default: server config)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 21, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations are all false, but the description explicitly states 'asynchronously and return a job_id', which discloses non-blocking behavior and output. This adds information beyond annotations without contradiction.

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?

Single sentence, no redundancy, includes all essential elements: execute, previously configured, asynchronous, job_id. Perfectly concise.

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?

Mentions the output (job_id) despite no output schema, covering the immediate result. Does not detail job polling but that is not required for the action itself. Adequate for context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema already fully describes both parameters (config_id from configure functions, max_parallel with default). The description does not add further parameter-specific details; baseline applies due to high schema coverage.

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

Purpose5/5

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

Clearly states the action (execute) and resource (Monte Carlo analysis), distinguishing it from siblings like run_sweep or configure_montecarlo. Mentions async and job_id, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Indicates that the analysis must be 'previously configured', implying a prerequisite step (configure_montecarlo). While it doesn't explicitly contrast with alternatives, the name and context make its intended use clear enough.

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