Filesystem MCP

monitor_get_cpu_info

Read-onlyIdempotent

Provides CPU core counts, optional frequency, and per-core usage to monitor system performance.

Instructions

Core counts, optional frequency, and per-CPU usage.

Return Format

{"success": bool, "result": {"physical_cores": int, "total_cores": int, "frequency": {...} | None, "usage_per_cpu": [float]}}

Examples

monitor_get_cpu_info()

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "monitor_get_cpu_info"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv3.1.0Oct 25, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already establish this as a read-only, idempotent, non-destructive, closed-world query. The description adds useful behavioral detail by disclosing the exact result shape and noting that frequency may be absent.

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?

It is front-loaded with the core purpose, then gives the return format and a minimal example. There is no filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-argument read-only tool with annotations and an output schema, the description is complete enough to call correctly. It even includes the return shape, making the result fully predictable.

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?

The tool has zero input parameters, so the baseline is 4. The description does not need to explain inputs, and its mention of optional frequency refers to the return value rather than an input parameter.

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 specific resource and returned data: physical/total core counts, optional frequency, and per-CPU usage. It is clear but does not explicitly differentiate itself from nearby monitoring siblings like monitor_get_resource_usage or monitor_get_system_status.

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?

The description gives no guidance on when to use this CPU-specific tool versus the other monitoring tools. The example only shows an empty invocation, not a usage context or alternative.

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