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rigol

rigol

by sparkybrit
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_waveform

Read-onlyIdempotent

Read a Rigol oscilloscope channel's on-screen trace (1200 points), save it as a CSV (time_s, volts), and return summary stats and file path. Clipped traces have unreliable extremes.

Instructions

Read one channel's on-screen trace (1200 points), save it as CSV (time_s,volts) and return summary statistics plus the CSV path. clipped: true means the trace ran off screen, so its extremes are unreliable. channel: 1-4 or CHAN1-CHAN4.

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": {
      "channel": "<channel>"
    },
    "name": "get_waveform"
  }
}

Input Schema

NameRequiredDescriptionDefault
channelYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds valuable behavior beyond that: the trace is limited to 1200 on-screen points, a CSV file is written to disk (a real side effect), and the `clipped` flag warns that extremes are unreliable when the trace runs off screen.

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

Conciseness5/5

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

Three tight sentences, each carrying distinct information (what it returns, the clipping caveat, the parameter format), front-loaded with the core action. No filler.

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

Completeness5/5

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

With no output schema, the description steps in to describe the return (summary stats plus CSV path) and the units (time_s, volts). Combined with the clipping caveat, an agent has everything needed to call and interpret this tool correctly.

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

Parameters5/5

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

Schema description coverage is 0%, so the description carries the full burden, and it does: it documents the accepted channel formats (1-4 or CHAN1-CHAN4). For the single required parameter this fully compensates for the schema 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?

States a specific verb and resource (read one channel's on-screen trace) with concrete scope (1200 points, CSV output, summary stats). This is clearly distinguishable from siblings like measure, screenshot, or scpi_query.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by describing the output and the cached-trace model, but it never says when to prefer this over `measure` (numeric measurements) or `screenshot` (image capture), which are the closest alternatives. No exclusions or prerequisites are given.

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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