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service_create

Create a Docker Swarm service for replicated or global scheduling, rolling updates, and automatic restart across the cluster.

Instructions

Create a Swarm service; requires a swarm manager node.

Use this instead of container_run when you need replicated or global scheduling, rolling updates, or automatic restart across the swarm. Common extra_kwargs keys: name (str), env (list of "KEY=VAL"), mode ({"Replicated": {"Replicas": N}} or {"Global": {}}), networks (list of network names/ids), endpoint_spec ({"Ports": [{"PublishedPort": 80, "TargetPort": 8080}]}), labels (dict), restart_policy ({"Condition": "on-failure", "MaxAttempts": 3}), resources ({"Limits": {"NanoCPUs": 500000000, "MemoryBytes": 134217728}}).

args: image - Image to run service tasks from (e.g. "nginx:alpine") command - Override the image's default command; string or list of strings extra_kwargs - Additional docker-py ServiceCollection.create keyword arguments returns: dict - The created service's attrs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
commandNo
extra_kwargsNo
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=false), the description adds critical behavioral context: 'requires a swarm manager node' and details the effects of `extra_kwargs` like mode and restart_policy, enhancing transparency.

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 a clear order: purpose, usage guidance, common extra_kwargs, parameter list, return value. It is front-loaded but the lengthy enumeration of extra_kwargs keys adds some verbosity.

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 the tool's complexity (3 params, nested objects, no output schema), the description covers parameter semantics, usage guidance, and return type adequately. It lacks explicit disambiguation from other service tools like `service_update`, but the create/update distinction is implicit.

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, type variations (e.g., command can be string or list), and providing concrete examples for `extra_kwargs` keys and their nested structures.

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 explicitly states 'Create a Swarm service' using a specific verb and resource, and it distinguishes the tool from its sibling `container_run` by explaining when to use it instead.

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 provides clear guidance on when to use this tool over `container_run` (for replicated/global scheduling, rolling updates, automatic restart), but does not mention other alternatives like `service_update` or `service_scale`.

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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