Skip to main content
Glama

container_logs

Tail Docker container logs in real time to diagnose issues, with options for line count, timestamp filters, and text or JSON format.

Instructions

Tail logs from a Docker container

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesContainer ID or name
tailNoNumber of lines to tail (default 100)
sinceNoShow logs since timestamp (e.g. '2024-01-01T00:00:00Z' or '10m')
formatNoOutput formattext
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'tail logs' without explaining whether it streams continuously, returns only the tail count, requires the container to be running, or how the 'since' parameter affects results. The agent is left to infer these behaviors from the schema.

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 sentence with no wasted words, directly stating the tool's purpose. It is front-loaded and appropriately sized for its simplicity.

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?

The tool has no output schema and no annotations, leaving the description as the primary source of context. The one-line description is insufficient for an agent to understand the return format, edge cases, or when to apply this tool relative to sibling tools. The schema covers parameters but does not compensate for the lack of high-level context.

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 descriptions cover 100% of the parameters (id, tail, since, format), so the baseline of 3 is appropriate. The description adds no additional parameter semantics beyond what the schema already provides.

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 'Tail logs from a Docker container' clearly identifies the tool's function (retrieving logs) and resource (Docker container), distinguishing it from sibling tools like start_container or docker_stats which have different purposes. It is specific and unambiguous.

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?

No guidance is provided on when to use this tool versus alternatives. The description lacks any mention of scenarios, prerequisites, or exclusions, such as when to use docker_stats instead for resource monitoring.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DTG404/infra-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server