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Create Coolify Service

coolify_create_service

Create a new service from a Docker Compose definition or a one-click template. Supply the docker-compose.yml content for custom services.

Instructions

Create a new service from a Docker Compose definition or a one-click template. For Devon's Flavor C apps (like Contact Hub), supply the docker-compose.yml content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoService display name
typeYesService type — use a one-click template name or 'docker-compose' for custom compose
revealNoReveal redacted secret values in the response (default false; the call is audited)
domainsNoFQDN for the service
instanceYesREQUIRED — which Coolify instance to mutate: 'prod' (Hetzner VPS) or 'dev' (local OrbStack VM). No default: state the target explicitly so a write never lands on prod by accident.
descriptionNoService description
server_uuidYesServer UUID
project_uuidYesUUID of the target project
destination_uuidYesDestination UUID
environment_nameNoEnvironment nameproduction
docker_compose_rawNoRaw docker-compose.yml content (required if type is docker-compose)
Behavior3/5

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

Annotations already declare the tool is not read-only and not destructive. The description adds that it creates a service, which implies mutation, but does not disclose additional behavioral traits like authentication needs, rate limits, or side effects on existing resources. The description provides minimal extra value 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 two sentences, front-loaded with the core purpose, and includes a specific use case without extraneous words. Every sentence earns its place.

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 has 11 parameters and no output schema, the description covers the main creation methods (compose/template) and a practical example. It does not address the instance field or type-dependent parameter requirements in detail, but the input schema handles that. Overall, it is fairly complete for a creation tool with good schema coverage.

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

Parameters3/5

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

Schema description coverage is 100%, so parameters are already well-documented. The description adds a contextual note about Flavor C apps but does not enhance understanding of individual parameters beyond what the schema provides. Baseline 3 is appropriate.

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 a new service from a Docker Compose definition or a one-click template. It distinguishes from sibling tools like coolify_create_application_dockercompose by specifying 'service' and provides a specific example (Flavor C apps), making the 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 Guidelines4/5

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

The description indicates when to use this tool (create a service via compose or template) and gives a concrete scenario. However, it does not explicitly exclude cases (e.g., when to use application creation tools instead) or mention prerequisites beyond what the schema already requires. Still, the context is clear.

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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