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ltspice-mcp

ltspice-mcp

by xuio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

getVectorData

Retrieve vector data from LTspice simulations, with optional interpolation at explicit points, for analyzing circuit performance.

Instructions

Get data for vectors, optionally interpolated at explicit scale points.

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": {
      "vectors": "<vectors>"
    },
    "name": "getVectorData"
  }
}

Input Schema

NameRequiredDescriptionDefault
vectorsYes
plotNo
run_idNo
raw_pathNo
step_indexNo
pointsNo
representationNoauto
max_pointsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.32.0

TDQS

C2.4/5.0
Behavior2/5

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

No annotations provided, so description must carry full behavioral disclosure. It mentions interpolation but omits default behavior, data limits, error cases, or performance implications. The tool has 8 parameters but the description gives no insight into their impact.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise—one sentence. No redundant content, but for an 8-parameter tool the brevity sacrifices informativeness. Could be expanded without losing conciseness.

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?

With 8 parameters, no annotations, and no param documentation, the description leaves the agent with almost no understanding of how to use the tool effectively. The existence of an output schema does not compensate for the lack of input guidance.

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%, yet the description only mentions 'vectors' and 'explicit scale points' (points) implicitly. It does not explain plot, run_id, raw_path, step_index, representation, or max_points. The description adds negligible value beyond the schema.

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 clearly states the tool retrieves data for vectors with optional interpolation at scale points. It distinguishes from sibling 'getVectorsInfo' which likely returns metadata. However, 'data' is vague; could specify 'values' or 'samples'.

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 guidance on when to use this tool vs alternatives like getVectorsInfo or getPlotNames. No context about prerequisites or typical use cases.

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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