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ryanmat

io.github.ryanmat/logicmonitor

by ryanmat

get_trace_service_metrics

Read-onlyIdempotent

Retrieve APM service-level RED metrics, including duration, error operation count, and operation count, for a specified service and time range.

Instructions

Get APM service-level 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_idYesInstance 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, openWorldHint, idempotentHint, and destructiveHint=false, covering the safety profile. The description adds the RED metric names but does not disclose behavioral details like time-range defaults, aggregation behavior, or required prerequisites.

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 sentence with no filler. It front-loads the action and resource, then gives concrete metric names, making every word informative.

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 metrics lookup with strong annotations and fully described parameters, the description is mostly sufficient for an agent to select and invoke the tool. However, there is no output schema and no mention of default time ranges or return value structure, leaving minor ambiguity around invocation details.

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?

The input schema has 100% property coverage with descriptions for all six parameters, so the schema carries the semantic burden. The description adds the datapoint names, which likely maps to the 'datapoints' parameter, but it does not explain parameter relationships or defaults beyond the schema.

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 uses a specific verb ('Get') with a clear resource ('APM service-level RED metrics') and enumerates the exact metric names (Duration, ErrorOperationCount, OperationCount). The phrase 'service-level' helps distinguish it from sibling operation-level metric tools like get_trace_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 description implies its use case through 'service-level RED metrics' but does not explicitly state when to use it instead of alternatives such as get_trace_operation_metrics or get_trace_service_properties. There are no clear exclusions or routing hints.

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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