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LTspice MCP

LTspice MCP

by kh6570
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Resolve Model Libraries

resolve_model_libraries
Read-onlyIdempotent

Search the workspace and LTspice library tree to find where a model name is defined, helping locate its library path for simulation.

Instructions

Search the workspace and the LTspice lib tree for a model name.

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": {
      "model_name": "<model_name>"
    },
    "name": "resolve_model_libraries"
  }
}

Input Schema

NameRequiredDescriptionDefault
model_nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.1

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description usefully adds the search scope (workspace plus LTspice lib tree), but says nothing about matching semantics (exact vs partial, case sensitivity) or what the result looks like.

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 scope (workspace, lib tree) comes before the target. It is efficient, though the brevity borders on under-specification rather than tightness.

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

Completeness3/5

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

For a simple one-parameter read-only search, annotations cover the safety profile, but with no output schema the description should explain what resolution returns (paths? matching libraries? ranked results?). That gap, plus undefined matching behavior, leaves it only minimally complete.

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 description coverage is 0% and the single property is a bare string, so the description carries the burden. It only conveys that the argument is a model name, adding no format, naming convention, or wildcard guidance beyond the property name itself.

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 ('Search') and the two resources it searches ('the workspace and the LTspice lib tree') plus the target ('a model name'). It is clear what the tool does, though it never contrasts itself with related tools like add_model or set_element_model.

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?

There is no explicit when-to-use guidance, no prerequisites, and no mention of alternatives. The only usage signal is implicit in the phrase 'for a model name', which tells the agent what input to supply but not when this tool is the right choice over listing or adding models.

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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