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container_stats

Monitor live CPU and memory usage of a running Docker container by providing its name.

Instructions

Shows live CPU and memory usage for a running container. Args: container_name: Docker Container name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
container_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of signaling behavior. The word 'Shows' implies a read-only operation, but the description does not explicitly state that no state is modified, nor does it mention potential failure modes (e.g., container not running) or permission requirements. It is accurate but lacks explicit transparency.

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?

The description is extremely concise, consisting of two short sentences. It states the purpose and the argument with no extraneous words. The structure is clean and easy to parse.

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 simple read-only tool with a single parameter, the description is adequately complete. It tells the user what the tool does and what input it needs. It does not describe the output format (e.g., JSON metrics), but this is not strictly required for a tool of this simplicity, and the sibling context suggests a standard metrics output.

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?

The only parameter, container_name, is described as 'Docker Container name,' which matches the schema title. This is clear for a simple identifier, but the description adds no additional context (e.g., format, name vs. ID, or that the container must exist). It does not go beyond the schema's minimal information.

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 the tool's function: 'Shows live CPU and memory usage for a running container.' It uses the specific verb 'Shows' and identifies the resource (CPU/memory usage) and target (running container), distinguishing it from sibling tools that handle logs, inspection, or execution.

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 provides no guidance on when to use this tool versus alternatives. It does not mention, for example, that it is preferable to container_inspect for live metrics, or that it requires a running container. Users are left to infer usage context from the description alone.

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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