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LTspice MCP

LTspice MCP

by kh6570
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Measure Waveform

measure_waveform
Read-onlyIdempotent

Measure avg, rms, max, min, pp, or peak on a specified signal from a raw waveform file, returning the computed value for analysis.

Instructions

Measure avg, rms, max, min, pp, or peak.

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": {
      "raw_path": "<raw_path>",
      "signal": "<signal>",
      "method": "<method>"
    },
    "name": "measure_waveform"
  }
}

Input Schema

NameRequiredDescriptionDefault
methodYes
signalYes
raw_pathYes
workspace_rootNoOptional per-call workspace root override.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.1

TDQS

C2.9/5.0
Behavior2/5

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is covered. The description adds nothing behavioral beyond the metric list: it says nothing about return format, units, error conditions, or what raw_path/signal must resolve to.

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 terse sentence with the metric enumeration front-loaded. No waste, though the extreme brevity edges toward under-specification rather than tight 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?

A 4-parameter measurement tool with three undocumented required params and no output schema. The description should clarify what signal and raw_path refer to and what a measurement returns; as written it is inadequate for correct invocation.

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 coverage is only 25% (just workspace_root), so the description must compensate. It does define the allowed method values (avg, rms, max, min, pp, peak), which is genuine value since no enum exists, but it leaves signal and raw_path entirely unexplained.

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 (measure) with an explicit list of supported metrics (avg, rms, max, min, pp, peak) on a waveform. This distinguishes it from more specialized siblings like measure_bode_response or measure_step_response, though it never explicitly says it operates on a waveform signal rather than, say, a full response curve.

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 versus alternatives such as read_waveform, evaluate_waveform_expression, read_measures, or compute_thd. The agent must infer usage entirely from the metric list.

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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