uni-t-uts-mcp

set_trace_math

Idempotent

Configure a spectrum analyzer trace's math operation to combine two operand traces for power difference/sum or log difference/offset, apply an optional dB offset, or turn math off.

Instructions

Set trace math for a trace (:CALCulate:MATH): result trace <- operand_a (op) operand_b. Operations: off, power_difference, power_sum, log_difference, log_offset; offset_db (-100..100) applies only to the two log operations. The instrument has no query for the math setting, so it cannot be read back (check the trace data). Enabling math switches the trace on (update and display); turning it off does not switch it off again.

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": {
      "trace": "<trace>",
      "operation": "<operation>"
    },
    "name": "set_trace_math"
  }
}

Input Schema

Name	Required	Description
`trace`	Yes	Trace (1-6) the operation is applied to
`offset_db`	No	Offset in dB, only for log_difference and log_offset (default 0)
`operand_a`	No	Operand A trace (1-6); required unless operation is off
`operand_b`	No	Operand B trace (1-6); required unless operation is off
`operation`	Yes	Math operation
`instrument`	No	Which instrument to use (a name from list_instruments). Default: the `default` instrument, or the only one configured

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.1.0Nov 13, 2026

TDQS

A3.9/5.0

Behavior3/5

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

The annotations already declare readOnlyHint=false and idempotentHint=true. The description adds genuinely useful behavior beyond that: there is no query to read the math setting back, enabling math force-enables the trace, and turning math off does not turn the trace off. Side effects on trace/display state are covered, but it says nothing about error or validation behavior.

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?

Dense and front-loaded: identity, operations, parameter constraints, then the readback caveat and side effects. Every sentence carries information, though the parenthetical SCPI reference and the stacked clauses make it slightly dense for a single paragraph.

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

Completeness4/5

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

No output schema, so the description could say what the response contains, but it compensates by telling the agent to check trace data for verification. Combined with the side-effect notes and full parameter documentation, it covers what an agent needs to call this mutation correctly; only response shape is unaddressed.

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 100%, so the ranges, enum, and per-parameter notes are already documented. The description adds the operand formula, which clarifies how trace, operand_a, and operand_b relate, but it mostly restates the offset and operand requirements the schema already states. Baseline 3 is appropriate.

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 ('Set trace math for a trace') and immediately pins it down with the SCPI node (:CALCulate:MATH) and the exact formula result <- operand_a (op) operand_b. Nothing about the purpose is left ambiguous.

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

Usage Guidelines4/5

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

Gives clear conditions for parameter use: the offset applies only to the two log operations, and the operation list defines what each choice does. It also tells the agent to verify results via trace data since the setting cannot be queried. It does not name an alternative tool, but no sibling appears to overlap, so this is context rather than a missing exclusion.

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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