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deploy_docker_local

Deploy a project locally with Docker and Docker Compose by auto-generating Dockerfile and docker-compose.yml, with optional PostgreSQL, MongoDB, and Redis containers.

Instructions

Deploy the project locally using Docker/Docker Compose. Auto-generates Dockerfile and docker-compose.yml. Can include PostgreSQL, MongoDB, and Redis containers. Requires Docker to be installed and running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
portNoPort to expose
buildNoBuild images before starting
detachNoRun in background
envVarsNoAdditional environment variables
withRedisNoInclude Redis container
projectPathYesAbsolute path to the project
serviceNameNoDocker service nameapp
withMongoDBNoInclude MongoDB container
withPostgresNoInclude PostgreSQL container
dockerfilePathNoCustom Dockerfile path (auto-detected if not set)
generateComposeNoGenerate docker-compose.yml
generateDockerfileNoGenerate Dockerfile if none exists
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It does mention that Dockerfile and docker-compose.yml are auto-generated and that optional containers (PostgreSQL, MongoDB, Redis) can be included, but it omits important side effects like modifying or overwriting existing project files, starting long-running processes, or what happens if Docker is not available.

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 three sentences long, front-loaded with the core action, and contains no redundant or filler content. Each sentence adds useful context: what it does, what it generates, and a prerequisite.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This tool has 12 parameters, no output schema, and no annotations, yet the description is very brief. It lacks crucial context about what happens after deployment (e.g., how to access the app, whether the command blocks or returns immediately), potential file modifications, and failure modes beyond the Docker prerequisite. The schema covers parameter meaning but not the overall deployment behavior.

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 input schema already documents all 12 parameters. The description adds limited extra meaning by explicitly naming the supported database containers and auto-generated files, but it does not go beyond what the schema descriptions already convey.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states what the tool does: deploys the project locally using Docker/Docker Compose, with auto-generated Dockerfile and compose file. It is specific about the resource (local Docker deployment) and differentiates from cloud deployment siblings like deploy_to_vercel and deploy_to_railway, though it does not explicitly contrast with the similar sibling 'deploy_local'.

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?

It explicitly states the prerequisite that Docker must be installed and running, and the scope ('locally using Docker') gives context for when to use this tool versus cloud-based alternatives. However, it does not provide exclusions or guidance on when NOT to use it (e.g., when the project is not Docker-compatible).

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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