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get_cluster_infrastructure_health

Check real-time CPU, RAM, and Docker container counts across Ubuntu hosts to identify resource bottlenecks and ensure cluster stability.

Instructions

Collects real-time CPU utilization, RAM usage, and active Docker container counts across all configured Ubuntu hosts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does disclose that data is real-time, scoped to all configured Ubuntu hosts, and limited to CPU, RAM, and Docker container counts. It does not explicitly state whether the operation is read-only, describe potential side effects, error conditions, or output shape, so some behavioral detail is still missing.

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?

A single well-structured sentence conveys the action, the data collected, and the scope. Every word contributes meaning, and the most important information is front-loaded. No filler or repetition.

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 zero-parameter, read-style monitoring tool, the description is largely complete: it names the exact metrics and host scope. The main gap is the lack of explicit return-format or usage-context details, but the low complexity of this tool means an agent can reasonably infer how to invoke it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so per the rubric the baseline is 4. The description appropriately focuses on what data is collected rather than parameter details, since there is no input schema to clarify.

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 uses a specific verb ('Collects') and a specific resource ('cluster infrastructure health') with concrete metrics: CPU utilization, RAM usage, and active Docker container counts. It is clear and likely distinguishable from get_cluster_hardware_analytics, though it does not explicitly name the sibling or draw the contrast.

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 usage: call this when you need real-time resource metrics across the Ubuntu hosts. However, it provides no explicit guidance about when to prefer this tool over related siblings like get_cluster_hardware_analytics or check_indexer_health, and no exclusions or alternative routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.