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Get CPU information

get_cpu_information
Read-only

Retrieve CPU details from local or remote Linux hosts to troubleshoot performance and diagnose hardware issues.

Instructions

Get CPU information.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostNoRemote host to connect to via SSH

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo
cpu_lineNo
load_avg_1mNo
load_avg_5mNo
load_avg_15mNo
frequency_mhzNo
logical_coresNo
physical_coresNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv1.6.0
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true, so the read-only nature is known. The description adds no additional behavioral context beyond what the annotation and schema already provide—no mention of SSH behavior when host is provided, no note about possible latency, and no details about what 'CPU information' includes. It is not contradictory, but it contributes no extra transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, but this is under-specification rather than effective brevity. The one sentence merely restates the tool name/title and does not include any additional context that would help an agent select or invoke the tool. It lacks the precision expected for a useful description.

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

Completeness2/5

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

Although an output schema exists and the parameter schema is complete, the description omits crucial context such as what specific CPU metrics are returned, how the host parameter affects execution, and how this differs from overlapping sibling tools. Given the large set of similarly named information-gathering tools, this description is insufficient for confident tool selection.

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%, with the single host parameter clearly documented as 'Remote host to connect to via SSH'. The description itself adds no parameter-level insight, but the schema fully compensates. The default null behavior is present in the schema, so the agent has enough to understand the parameter's semantics.

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?

States a specific verb and resource: 'Get CPU information.' It clearly identifies the intended action and object, but it does not differentiate from sibling tools like get_hardware_information or get_system_information, which could also return CPU-related data. The lack of scope details (e.g., utilization, architecture, cores) leaves some ambiguity, but the core purpose is unmistakable.

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?

Provides no guidance on when to use this tool versus the many sibling tools (get_memory_information, get_hardware_information, etc.). There is no mention of prerequisites, scenarios, or exclusions. The agent must infer usage solely from the tool's name.

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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