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compose_ps

Read-only

List containers in a Docker Compose project, showing state, health, and publishers. Use the 'all' flag to include stopped containers for a complete view.

Instructions

List containers in a compose project, parsed from --format json.

Container-level view of one project (state, health, publishers); compose_list enumerates projects, and container_list covers non-compose containers. Does not raise on a non-zero CLI exit: services comes back empty — inspect raw.stderr.

args: 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 services - Restrict output to these services all - Include stopped containers as well returns: dict - {"services": list[dict], "raw": }; on non-zero exit services is an empty list and the caller should inspect raw.stderr.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
allNo
filesNo
servicesNo
project_dirNo
project_nameNo
Behavior5/5

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

Annotations already provide readOnlyHint and destructiveHint, but the description adds valuable behavior: it does not raise on non-zero CLI exit, services comes back empty, and raw.stderr should be inspected. It also discloses that project_dir is copied to the target host if no local plugin. This goes well beyond 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 well-structured with a summary, usage context, args list, and return section. Each sentence adds value: the differentiation from siblings, the non-zero exit behavior, and parameter explanations. No redundant text or 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?

Despite lacking an output schema, the description fully specifies the return format (dict with services and raw) and error semantics. It covers argument semantics, remote behavior, and usage context, making it complete for a tool with 5 parameters and no output schema.

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 every parameter: project_dir (with default and remote behavior), files (repeatable -f), project_name override, services restriction, and all for including stopped containers. This provides meaning not present in the schema.

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 'List containers in a compose project' with a specific verb and resource. It explicitly distinguishes from sibling tools: compose_list enumerates projects, container_list covers non-compose containers. This makes the tool's purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance: 'Container-level view of one project' versus compose_list for projects and container_list for non-compose containers. It also explains behavior on non-zero CLI exit, advising inspection of raw.stderr, which helps callers handle edge cases.

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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