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service_create_from_image

Create a Railway service from a Docker image to deploy custom databases, pre-built containers, or specific image versions.

Instructions

[API] Create a new service from a Docker image

⚡️ Best for: ✓ Custom database deployments ✓ Pre-built container deployments ✓ Specific version requirements

⚠️ Not for: × Standard database deployments (use database_deploy) × GitHub repository deployments (use service_create_from_repo) × Services needing build process

→ Prerequisites: project_list

→ Alternatives: database_deploy, service_create_from_repo

→ Next steps: variable_set, service_update, tcp_proxy_create

→ Related: volume_create, deployment_trigger

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesID of the project to create the service in
imageYesDocker image to use (e.g., 'postgres:13-alpine')
nameNoOptional custom name for the service
Behavior3/5

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

No annotations are provided, so the description carries full burden. It mentions prerequisites and next steps, which adds useful context, but lacks details on behavioral traits like permissions needed, rate limits, or what happens on creation (e.g., default settings, costs). The description doesn't contradict annotations, but could be more informative for a creation tool.

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 with bullet points and symbols, front-loaded with the core purpose. Every sentence adds value (e.g., use cases, exclusions, prerequisites), with no wasted words, making it efficient and easy to scan.

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 annotations and no output schema, the description does well by covering purpose, guidelines, and context (prerequisites, next steps). However, as a creation tool, it could benefit from more behavioral details (e.g., response format, error handling) to be fully complete, though it's largely adequate.

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 the schema already documents all parameters. The description doesn't add specific meaning beyond the schema (e.g., format examples for image beyond what's in schema, or implications of optional name). Baseline 3 is appropriate as the schema does the heavy lifting.

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 image, specifying both the action (create) and resource (service from image). It distinguishes from sibling tools like service_create_from_repo and database_deploy, making it specific and differentiated.

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?

The description provides explicit guidance with 'Best for' and 'Not for' sections, naming alternatives (database_deploy, service_create_from_repo) and stating prerequisites (project_list). This gives clear context on when to use this tool versus others.

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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