AI tools work better when they understand the setup. Here’s how to document Compose files effectively.

Add context with comments

Comments help AI understand what each service does:

services:
  # Primary web application serving React frontend
  # Handles user authentication and API gateway
  web:
    image: myapp:latest
    ports:
      - "3000:3000"  # Public facing port - update in .env for production
    environment:
      # Connection string to PostgreSQL - format: postgresql://user:pass@host:5432/db
      DATABASE_URL: ${DATABASE_URL}
      # JWT secret for auth - must be at least 256 bits
      JWT_SECRET: ${JWT_SECRET}
    depends_on:
      db:
        condition: service_healthy
    # Development only - remove for production
    volumes:
      - ./src:/app/src  # Hot reload for development

  # PostgreSQL 15 database with PostGIS extension
  # Stores user data and geographic information
  db:
    image: postgis/postgis:15-3.3
    environment:
      POSTGRES_DB: myapp
      POSTGRES_PASSWORD: ${DB_PASSWORD}  # Never commit actual password
    volumes:
      # Initial schema and seed data
      - ./init.sql:/docker-entrypoint-initdb.d/01-init.sql
      # Persistent data storage
      - postgres_data:/var/lib/postgresql/data

volumes:
  postgres_data:
    # Named volume for database persistence across container restarts

File headers

For bigger projects, add a header:

# Application: E-commerce Platform
# Environment: Development
# Required: Docker 24.0+, Compose v2.20+
#
# Services:
# - web: Next.js frontend (port 3000)
# - api: Node.js backend (port 4000)
# - db: PostgreSQL database
# - redis: Session cache
#
# Quick Start:
# 1. cp .env.example .env
# 2. docker compose up -d
# 3. Visit http://localhost:3000

name: ecommerce-dev

services:
  # ... services

Document environment variables

services:
  api:
    environment:
      # Required: External service credentials
      STRIPE_API_KEY: ${STRIPE_API_KEY:?Missing STRIPE_API_KEY}

      # Optional: Defaults provided
      LOG_LEVEL: ${LOG_LEVEL:-info}  # Options: debug, info, warn, error

      # Feature flags
      ENABLE_BETA_FEATURES: ${ENABLE_BETA:-false}  # Set to true for beta testing

Useful patterns

Describe relationships:

worker:
  # Processes background jobs from Redis queue
  # Depends on: api (for job creation), redis (for queue)

Explain your choices:

nginx:
  image: nginx:alpine  # Alpine: 5MB vs 142MB regular

Mark the tricky parts:

volumes:
  - ./data:/data  # WARNING: Check ownership (1000:1000)

What AI can do with this

When your files are documented, AI tools can:

  • Write health checks that make sense
  • Spot security issues
  • Generate CI/CD configs
  • Create test setups
  • Suggest performance improvements

Example prompt

“Generate a production version of this Compose file with security improvements”

The AI uses your comments to understand what needs protecting and what to remove.

Extra tip

Create an AI-CONTEXT.md file:

# Project Context for AI

## Architecture
- Microservices with REST APIs
- PostgreSQL for persistent data
- Redis for caching
- nginx for reverse proxy

## Conventions
- Port 3xxx for frontend services
- Port 4xxx for backend services
- All services run as non-root

Then reference it:

# See AI-CONTEXT.md for project details
services:
  # ...