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compose_stop

Stop services in a Docker Compose project without removing containers, networks, or volumes, allowing them to be resumed later.

Instructions

Stop services in a compose project without removing their containers.

Unlike compose_down, containers/networks/volumes survive — use compose_start to bring them back.

args: project_dir - Dir with the compose file (default: server cwd) files - Explicit compose file paths (repeatable, -f) project_name - Compose project name override services - Specific services to stop (default: all) stop_timeout_seconds - Grace period before SIGKILL (passed as --timeout) timeout_seconds - Subprocess timeout (default 300s) returns: dict - {"returncode": int, "stdout": str, "stderr": str, "truncated": bool}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filesNo
servicesNo
project_dirNo
project_nameNo
timeout_secondsNo
stop_timeout_secondsNo
Behavior4/5

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

Annotations only indicate non-read-only and non-destructive hints. The description adds crucial behavioral context: containers/networks/volumes survive, the existence of grace period (stop_timeout_seconds) before SIGKILL, and subprocess timeout behavior. This goes beyond annotations without contradicting them.

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 concise, front-loading the purpose in the first sentence, then using bullet points for parameters. Every sentence adds value without redundancy. The structure is efficient and easy to scan.

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?

Given six parameters and no output schema, the description provides sufficient detail on behavior, parameter semantics, and return format (dict with returncode, stdout, stderr, truncated). It lacks information about potential errors or side effects, but covers the essential aspects for an agent to use the tool correctly.

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?

With 0% schema description coverage, the description fully compensates by explaining each parameter's purpose: project_dir, files, project_name, services, stop_timeout_seconds (passed as --timeout), and timeout_seconds (default 300s). It adds value by clarifying how each parameter affects behavior, such as the subprocess timeout.

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 stops services in a compose project without removing containers, distinguishing it from compose_down which removes containers. It uses specific verbs ('stop services') and resource ('compose project'), effectively differentiating from sibling tools like compose_down and compose_start.

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 explicitly contrasts with compose_down and recommends compose_start to bring services back. However, it doesn't compare to other stop tools like stop_container or mention when to stop specific services vs all. Still, it provides clear context on when to use this tool versus its primary alternative.

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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