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sandraschi

oscilloscope-mcp

scope_configure

Configure oscilloscope channel settings and simulator signal profiles to prepare your measurement setup and generate test waveforms.

Instructions

Configure oscilloscope channels and simulator signal profiles.

Return Format

{"success": bool, "operation": str, "data": {...}}

Examples

  • scope_configure(operation="channel", channel_id="A", range_v=2.0, coupling="dc")

  • scope_configure(operation="get")

  • scope_configure(operation="simulator_profile", waveform="square", frequency_hz=1000)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
enabledNoEnable or disable channel.
range_vNoFull-scale voltage range in volts.
couplingNoInput coupling: dc or ac.
offset_vNoAnalog offset in volts.
waveformNoSimulator waveform type (simulator_profile only).
operationYesConfiguration operation.
channel_idNoChannel label (A, B, CH1).
amplitude_vNoSimulator amplitude in volts.
frequency_hzNoSimulator frequency in Hz.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint=false and destructiveHint=false, so the mutating nature is known. The description adds a return format and concrete examples, which help an agent understand what to expect, but it does not disclose side effects such as overwriting existing settings or any device prerequisites. Some context is added, but the behavioral picture is incomplete.

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?

The description is compact and well-structured with a one-line purpose, a return format section, and three illustrative examples. Every part earns its place and there is no fluff or redundant detail.

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?

The description covers three of the four operations in the enum but omits an example or explanation for 'channels'. The return format is generic, and there is no output schema to clarify the data field. Given 9 parameters and 4 operations, the description provides a usable but incomplete picture for all possible invocations.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds value by showing parameter-to-operation mappings through examples: channel_id/range_v/coupling for 'channel', waveform/frequency_hz for 'simulator_profile', and no params for 'get'. This helps an agent combine parameters correctly beyond the raw schema descriptions.

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?

The description states a specific verb and resource: 'Configure oscilloscope channels and simulator signal profiles.' The examples further clarify distinct operations. The tool name and resource clearly differentiate it from sibling tools like scope_capture, scope_measure, and scope_trigger.

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?

The description gives clear context that this tool is for configuration rather than capture or measurement, but it does not explicitly say when to use this tool versus alternatives, nor does it mention any exclusions. Usage is implied through the examples and operation enum rather than stated directly.

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