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ryanmat

io.github.ryanmat/logicmonitor

by ryanmat

get_cost_recommendations

Read-onlyIdempotent

Fetch cost optimization recommendations from LogicMonitor. Filter by category, status, and pagination to identify idle AWS EC2 instances and other savings opportunities.

Instructions

Get cost optimization recommendations. Category filter takes the category description string from get_cost_recommendation_categories

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results
offsetNoResults to skip for pagination
statusNoFilter by recommendation status (e.g. active)
categoryNoCategory description string (e.g. "Idle AWS EC2 instances")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.2.0

TDQS

B3.1/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. However, the description adds no behavioral context beyond this—no mention of pagination defaults, ordering, response shape, or what happens when no filters are supplied. It does not contradict the annotations, but it provides no additional transparency.

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, no filler. The main purpose is stated firstain and the category-filter dependency is a useful addition. Every word 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?

For a simple read-only list call with fully documented parameters and supportive annotations, this is close to sufficient. But the absence of an output schema and lack of guidance distinguishing it from the singular get_cost_recommendation leaves a small but real gap for an agent deciding which tool to invoke.

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 schema has 100% description coverage with clear descriptions for limit, offset, status, and category. The additional note that the category filter takes the description string from get_cost_recommendation_categories reinforces the schema example but adds only marginal value, so it stays at the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource: 'Get cost optimization recommendations.' It adds a useful pointer that the category filter uses description strings from get_cost_recommendation_categories. However, it does not distinguish this list operation from the sibling get_cost_recommendation (singular), so an agent could confuse which to call.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool instead of get_cost_recommendation or get_cost_recommendation_categories. The only usage hint is that the category parameter should use the description string from the categories endpoint, which is more of a parameter tip than a tool-selection guideline.

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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