ltspice-mcp

by xuio

Overview Schema Source Related Servers Discussions Admin

Python

Local

queueSimulationJob

Queue an LTspice simulation job and return a job ID for status polling or cancellation.

Instructions

Queue a simulation job and return a job id for status polling/cancelation.

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": "queueSimulationJob"
  }
}

Input Schema

Name	Required	Default
`netlist_path`	No
`netlist_content`	No
`circuit_name`	No	queued_job
`ascii_raw`	No
`timeout_seconds`	No
`priority`	No
`max_retries`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.32.0Jun 10, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the async behavior (return job id for polling/cancelation) but does not elaborate on error handling, timeout effects, or retries. Adequate but not rich.

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 description is a single concise sentence that front-loads the core purpose. It is efficient but could benefit from a brief expansion on parameter usage without losing conciseness.

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?

Given the complexity of 7 parameters and 0% schema coverage, the description is insufficient. It does not guide parameter selection, output handling (despite having an output schema), or integration with sibling tools like 'jobStatus' or 'cancelJob'.

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

Parameters1/5

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

Schema description coverage is 0%, and the tool description provides no explanations for the 7 parameters (e.g., netlist_path vs netlist_content, priority, timeout). The agent has no guidance on how to set these parameters, making this a critical gap.

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?

The description clearly states the verb 'queue' and resource 'simulation job', and adds the return value 'job id' for polling/cancellation. This distinguishes it from sibling tools like 'runSimulation' or 'simulateNetlist' which likely execute synchronously.

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?

The description implies usage for asynchronous job submission requiring later status polling or cancellation. It does not explicitly state when not to use it or list alternatives, but the context is clear enough for an AI agent.

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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