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ryanmat

io.github.ryanmat/logicmonitor

by ryanmat

get_trace_operation_metrics

Read-onlyIdempotent

Retrieve per-operation RED metrics for a service, including duration, error count, and operation count, to analyze performance and availability.

Instructions

Get per-operation RED metrics (Duration, ErrorOperationCount, OperationCount)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
end_timeNoEnd time in epoch seconds
datapointsNoComma-separated datapoint names (all if omitted)
service_idYesAPM service device ID
start_timeNoStart time in epoch seconds
instance_idYesOperation instance ID
device_datasource_idYesDevice datasource ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.2.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety behavior is covered. The description adds a little context by naming the return metric fields, but it does not disclose behavior such as time range handling, defaults, or response shape. With these annotations, a 3 is appropriate.

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 a single concise, front-loaded sentence with no filler. Every word contributes: the verb, the per-operation scope, the RED metrics concept, and the specific metric names. No redundant or vague phrasing exists.

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?

For a read-only, idempotent tool with 100% schema parameter coverage, the description is largely complete. It clarifies the return metric fields, which is important given no output schema is available. Minor gaps remain, such as the exact response shape and units for Duration, but these are not critical for invoking the tool correctly.

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 description coverage is 100%: all six parameters already have descriptions in the schema, including defaults for datapoints. The description adds no parameter-level information beyond the metric names it exposes, so the baseline of 3 applies.

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 clearly states the action ('Get'), resource ('per-operation RED metrics'), and lists the exact metric names (Duration, ErrorOperationCount, OperationCount). This differentiates it from sibling tools like get_trace_service_metrics, which targets service-level metrics rather than per-operation metrics.

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 phrase 'per-operation RED metrics' implies this tool is appropriate when per-operation metrics are needed, and the naming contrasts with get_trace_service_metrics. However, the description does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites.

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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