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container_create

Create a container from an image without starting it, allowing pre-start configuration via extra_kwargs. Start the container separately when ready.

Instructions

Create a container from an image without starting it.

Use this when you need to configure a container (with extra_kwargs) before its first start, or want creation and start as separate observable steps. For the common case of create-then-start-immediately use container_run instead — it does both in one call. Start the created container with container_start. Common extra_kwargs keys: name (str), environment (list of "KEY=VAL" or dict), ports (dict, e.g. {"80/tcp": 8080}), volumes (dict, e.g. {"/host/path": {"bind": "/container/path", "mode": "rw"}}), labels (dict). For anything else docker-py's ContainerCollection.create accepts, call docs_lookup(section="containers") rather than guessing a key name.

args: image - Image to create the container from, e.g. "nginx:alpine" command - Override the image's default command; string or list of strings extra_kwargs - Additional docker-py ContainerCollection.create keyword arguments returns: dict - The created container's attrs (not yet running)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
commandNo
extra_kwargsNo
Behavior5/5

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

Annotations show readOnlyHint=false and destructiveHint=false. The description adds that the container is not started, describes the return value as 'not yet running', and explains that extra_kwargs can include specific keys. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with purpose first, then usage guidance, then parameter details. It is slightly long due to listing extra_kwargs keys, but every sentence adds value. Minimal fluff.

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 no output schema, the description adequately explains the return value (dict of attrs). It also covers the main use case and parameter details. Could optionally mention errors or permissions, but not required for typical use.

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 has 0% description coverage. The description compensates fully: provides example for image, explains command override, and lists common extra_kwargs keys with formats (e.g., environment as list of KEY=VAL or dict). Also advises using docs_lookup for other keys.

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 'Create a container from an image without starting it.' It distinguishes from container_run (which creates and starts) and container_start, making the purpose 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 Guidelines5/5

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

Explicitly says when to use: for configuring before first start or separate observable steps. Provides alternative: container_run for create-then-start-immediately, and container_start to start after creation. This is thorough.

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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