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config_create

Create an immutable Swarm config to store non-sensitive configuration files (e.g., nginx.conf). Configs mount into service containers and cannot be modified after creation.

Instructions

Create an immutable Swarm config object; requires a swarm manager.

Configs store non-sensitive configuration files (nginx.conf, app.yaml, etc.) and mount them into service containers at a specified path. Unlike secrets, config data is not encrypted at rest — use secret_create for credentials or keys. data is raw bytes; encode strings first (e.g. "my config".encode()). Once created, a config is immutable: to update it, create a new config with a new name and update the service to reference it, then remove the old config with config_remove.

args: name - Unique config name within the swarm data - Raw bytes content of the config file labels - Labels to set on the config templating - Templating driver config (e.g. {"Name": "golang"} for Go template syntax) returns: dict - The created config's attrs including its id

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
nameYes
labelsNo
templatingNo
Behavior5/5

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

Beyond annotations (readOnlyHint=false, destructiveHint=false), the description details immutability, non-encrypted storage, data encoding requirements, and the update workflow. It also states the return type (dict with id). No contradiction with annotations.

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 fairly long but well-structured, front-loading the main purpose and then detailing behavior and parameters. Every sentence adds value, though slight compression could improve conciseness.

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?

Given no output schema, the description covers return type, immutability, encoding, encryption, and prerequisites (swarm manager). It fully addresses the tool's complexity and usage context.

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 compensates fully by explaining all four parameters: name (unique), data (raw bytes with encoding advice), labels (labels), templating (example given). This adds significant meaning beyond 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 the tool creates an immutable Swarm config object, specifies it stores non-sensitive configuration files, and distinguishes it from secret_create for credentials. The verb 'create' and resource 'config' are explicit.

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 mentions it requires a swarm manager and contrasts with secret_create for credentials. It advises encoding strings for the data parameter. However, it does not explicitly state when not to use this tool beyond the secret comparison.

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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