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zskycode
by zskycode

container_logs

Fetch Docker container logs to debug issues. Filter by line count, time range, and include timestamps to pinpoint errors.

Instructions

Fetch the logs of a container

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tailNoNumber of lines to show from the end of the logs (e.g. "100")
sinceNoShow logs since timestamp (e.g. "2021-01-02T13:23:37") or relative (e.g. "42m" for 42 minutes)
untilNoShow logs before timestamp (e.g. "2021-01-02T13:23:37") or relative (e.g. "42m" for 42 minutes)
containerYesContainer ID or name
timestampsNoShow timestamps

Schema Changelog

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

  1. First observedv0.3.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only states a basic fetch operation and does not mention output format, streaming behavior, whether logs are returned once or continuously, or any side effects. This is a significant gap given the absence of annotations.

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 a single, focused sentence with no filler. It states the core purpose efficiently and leaves parameter details to the schema, which is the ideal structure for a simple tool.

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

Completeness3/5

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

For a tool with no annotations and no output schema, the description plus fully documented schema is minimally viable, but it leaves out behavior such as return format and log-following semantics. An agent could call it correctly, but may be uncertain about what response to expect.

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 schema covers 100% of parameters with descriptions, so the description does not need to re-document them. It adds no extra meaning about defaults, parameter interactions, or format nuances, but the baseline of 3 is appropriate since the schema is complete.

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 uses a clear verb-resource pair: 'Fetch the logs' of 'a container'. It is unambiguous and differentiates from sibling tools by specifying container logs, though it does not explicitly distinguish itself from compose_logs.

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?

The intended use is implied by the name and description: when you need logs for a container. However, it provides no explicit guidance about when to prefer this over compose_logs or inspect_container, and no exclusions or alternatives are stated.

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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