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fenhuayue

local-tools-mcp-server

by fenhuayue

Get System Information

localtools_system_info
Read-onlyIdempotent

Retrieve OS, CPU, memory, uptime, and user details to understand the running environment.

Instructions

Retrieve basic system information including OS, CPU, memory, uptime, and user details.

Useful for understanding the environment the AI is running in. All information is read-only and comes from the Node.js os module.

Args:

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns:

  • OS type, platform, release version

  • CPU model and core count

  • Total and free memory

  • System uptime

  • Current user and home directory

  • Hostname

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readablemarkdown
Behavior4/5

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

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint. The description adds explicit detail: 'All information is read-only and comes from the Node.js os module.' This reinforces the annotations and provides source context, though there is no additional behavioral nuance beyond what annotations already cover.

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

Conciseness4/5

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

The description is well-structured with a clear lead sentence, a usage sentence, and separated Args and Returns sections. It is concise without extraneous text, though the Returns section could be slightly more streamlined. It earns a 4 for good structure and front-loading of purpose.

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 simple read-only tool with one optional parameter and no output schema, the description fully covers the return values by listing all expected fields (OS, CPU, memory, etc.). It also explains the source and behavior. There are no gaps given the tool's simplicity.

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 coverage is 100% with a description for the single parameter. The description repeats the parameter meaning ('Output format: markdown or json') in the Args section. This adds no new meaning beyond the schema, so a baseline 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 clearly states it retrieves basic system information (OS, CPU, memory, etc.) with a specific verb 'Retrieve'. It distinguishes the tool's purpose from any siblings (none present) and covers the full scope of what the tool does.

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

Usage Guidelines4/5

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

The description provides a clear usage context: 'Useful for understanding the environment the AI is running in.' While it doesn't explicitly state when not to use it or list alternatives, there are no sibling tools to compare against, so this is sufficient guidance.

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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