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ltspice-mcp

ltspice-mcp

by xuio
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

inspectSchematicVisualQuality

Evaluate schematic visual quality and recommend coordinate-level fixes to resolve issues.

Instructions

Inspect schematic visual quality and suggest coordinate-level fixes.

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": {
      "asc_path": "<asc_path>"
    },
    "name": "inspectSchematicVisualQuality"
  }
}

Input Schema

NameRequiredDescriptionDefault
asc_pathYes
renderNo
settle_secondsNo
downscale_factorNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.32.0

TDQS

C2.3/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It states 'inspect' and 'suggest fix', implying a read-only operation, but does not explicitly confirm or describe side effects, required permissions, or what happens if suggestions are applied.

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

Conciseness2/5

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

The description is very short but lacks substance. It is not concise in the sense of being efficiently informative; it is under-specified and does not earn its limited space.

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?

Given 4 parameters (1 required) and no parameter descriptions, the tool is severely incomplete. The output schema may document return values, but the input side is left completely to the agent's guess.

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 provides no information about any of the 4 parameters (asc_path, render, settle_seconds, downscale_factor). The agent receives no help in understanding parameter meaning or usage.

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?

Description clearly states the tool inspects schematic visual quality and suggests coordinate-level fixes. It distinguishes from siblings like autoCleanSchematicLayout (automatic cleaning) and lintSchematic (linting). However, 'coordinate-level fixes' is a bit vague.

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 versus alternatives like autoCleanSchematicLayout or validateSchematic. The description lacks explicit usage context or prerequisites.

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

Deploy Server

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