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service_create

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

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}}). For anything else docker-py's ServiceCollection.create accepts, call docs_lookup(section="services") rather than guessing a key name.

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 full document ({"ID", "Version", "Spec", ...})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
imageYes
commandNo
extra_kwargsNo
Behavior4/5

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

The description adds behavioral context beyond annotations (e.g., requires swarm manager, return format). Annotations already indicate readOnlyHint=false and destructiveHint=false, so the description does not contradict them and provides additional useful details.

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: purpose statement, usage guidance, parameter details with common keys, and return info. It is concise yet comprehensive, with no wasted sentences.

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 covers return values (dict with ID, Version, Spec). It addresses the complexity of docker-py's ServiceCollection.create by listing common extra_kwargs keys. Could mention error conditions or prerequisites but is fairly complete.

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

Parameters4/5

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

Despite 0% schema description coverage, the description explains image, command (including types), and extra_kwargs with common keys listed. This adds significant meaning beyond the raw 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 it creates a Swarm service and requires a swarm manager node. It distinguishes from container_run by listing specific use cases like replicated/global scheduling, rolling updates, or automatic restart across the swarm.

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 says when to use this tool instead of container_run and suggests using docs_lookup for unknown extra_kwargs keys. However, it does not explicitly state when not to use the tool (e.g., if the swarm is not initialized).

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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