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ryanmat

io.github.ryanmat/logicmonitor

by ryanmat

score_device_health

Read-onlyIdempotent

Score the health of a specific device-datasource instance using z-score analysis of historical metrics to detect anomalies, with optional datapoint weights and custom time windows.

Instructions

Score health of a specific device-datasource instance using z-score analysis. For full device health reports across all datasources, use the health_check composite tool instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
weightsNoOptional dict of datapoint_name -> weight
device_idYesDevice ID
datapointsNoComma-separated datapoint names (all if omitted)
hours_backNoHours of historical data for baseline
instance_idYesInstance ID
device_datasource_idYesDevice-DataSource ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.2.0

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already cover read-only, idempotent, open-world, and non-destructive behavior, which lowers the bar for additional disclosure. The description adds useful context about z-score methodology and per-instance scope, but does not explain the score's scale, meaning, or returned structure, which matters since there is no output schema.

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?

Two sentences with no filler. The first sentence front-loads the core action and method, and the second sentence provides actionable sibling routing. Everything in the description earns its place.

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?

Full schema parameter documentation and strong annotations cover invocation inputs and safety profile. However, with no output schema, the description should convey what the returned health score represents, such as its type, range, or interpretation, to be fully complete for an agent acting on the result.

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%, so every parameter is already documented in the input schema. The description adds no extra parameter syntax, defaults, or interrelationships beyond what the schema provides, so the baseline score of 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?

The description states a specific verb ('Score'), a precise resource ('specific device-datasource instance'), and a method ('z-score analysis'). It also differentiates the tool from the sibling health_check tool by explicitly directing full multi-datasource health reports elsewhere.

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

Usage Guidelines5/5

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

The description gives clear when-to-use guidance: score a single device-datasource instance. It also names the alternative, health_check, for full device health reports across all datasources, making the choice between siblings explicit.

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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