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info_sistema

Retrieves real system details such as OS, CPU, memory, disk, uptime, and Python version to verify that the local setup is working.

Instructions

Muestra informacion real del equipo: sistema operativo, procesador, memoria, disco, tiempo encendido y version de Python. Es la prueba mas rapida de que todo funciona.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden, but the tool takes zero parameters and is plainly a read-only informational call. The description usefully adds that it returns *real* (not mocked) machine data and frames it as a quick health probe, yet it says nothing about latency, sandboxing, or side effects.

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 short sentences, with the data payload front-loaded and the purpose framing second. No filler or redundant restatement of the tool name.

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?

With no parameters, no output schema, and no annotations, the description supplies everything an agent needs: the returned fields, the fact that values are real, and the practical reason to call it. Nothing material is missing for such a simple tool.

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, which is the baseline-4 case; there is nothing for the description to disambiguate. It does at least preview which values the response contains, adding a little value beyond the empty schema.

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 pairs a specific verb ("Muestra") with an enumerated set of resources (OS, processor, memory, disk, uptime, Python version), so the agent knows exactly what data comes back. None of the siblings (hora_actual, sumar, eco) overlap with this scope, making it distinguishable without opening any schema.

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?

"Es la prueba mas rapida de que todo funciona" implies a health-check/smoke-test use case, which is a genuine usage hint. However, it never names alternatives or states when not to use it, so guidance remains implied rather than explicit.

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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