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compose_top

Read-only

Show running processes for each service in a Docker Compose project, returning a ps-style process table. Use it to inspect active container processes.

Instructions

Show the running processes of a compose project's containers.

Output is the ps-style process table per service (not JSON); read it from stdout. The per-container equivalent is container_top. Does not raise on a non-zero CLI exit (a missing compose plugin or a timeout still raises) - inspect returncode/stderr in the result.

Args: services: Restrict to these services (default: all) project_dir: Dir with the compose file (default: server cwd; copied to the target host if no local plugin) files: Explicit compose file paths (repeatable, -f) project_name: Compose project name override

Returns: dict: {"returncode": int, "stdout": str, "stderr": str, "truncated": bool}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNo
servicesNo
project_dirNo
project_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.9.0

TDQS

A4.8/5.0
Behavior5/5

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

The annotations mark this as read-only and non-destructive, and the description adds substantial behavioral detail: output is ps-style text on stdout rather than JSON, non-zero CLI exits do not raise while missing plugin or timeout do, and returncode/stderr should be inspected. This goes well beyond the annotation hints and gives an agent realistic expectations.

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 structured with a short purpose sentence, a behavioral/error note, and compact Args/Returns sections. Every sentence earns its place: output format, error behavior, parameter meanings, and result shape are all necessary and presented without filler.

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 output schema, the Returns dict shape is explicitly provided. All optional parameters are explained, output format is identified as non-JSON stdout, and unusual error behavior is disclosed. Nothing essential for invoking compose_top correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry the burden for parameters. It defines all four: services restricts scope, project_dir supplies default and a copy-to-host behavior, files are repeatable and map to -f, and project_name is an override. Each parameter gets meaningful semantics beyond the bare schema definitions.

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 opens with a specific verb and resource: 'Show the running processes of a compose project's containers.' It further distinguishes itself by noting the per-container equivalent is container_top and clarifies the output is a ps-style process table per service, not JSON. This clearly separates it from siblings like compose_ps and container_top.

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 states clear context: use for compose project containers, with container_top named as the per-container equivalent. It does not enumerate when-not-to-use scenarios or compare against compose_ps, but the project-versus-container distinction gives enough guidance for an agent to select this tool correctly.

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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