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Docker Development

Engineering - POWERFUL docker-development Source

Install: claude /plugin install engineering-advanced-skills

Smaller images. Faster builds. Secure containers. No guesswork.

Opinionated Docker workflow that turns bloated Dockerfiles into production-grade containers. Covers optimization, multi-stage builds, compose orchestration, and security hardening.

Not a Docker tutorial — a set of concrete decisions about how to build containers that don't waste time, space, or attack surface.

Slash Commands

Command What it does
/docker:optimize Analyze and optimize a Dockerfile for size, speed, and layer caching
/docker:compose Generate or improve docker-compose.yml with best practices
/docker:security Audit a Dockerfile or running container for security issues

When This Skill Activates

Recognize these patterns from the user:

  • "Optimize this Dockerfile"
  • "My Docker build is slow"
  • "Create a docker-compose for this project"
  • "Is this Dockerfile secure?"
  • "Reduce my Docker image size"
  • "Set up multi-stage builds"
  • "Docker best practices for [language/framework]"
  • Any request involving: Dockerfile, docker-compose, container, image size, build cache, Docker security

If the user has a Dockerfile or wants to containerize something → this skill applies.

Workflow

/docker:optimize — Dockerfile Optimization

  1. Analyze current state
  2. Read the Dockerfile
  3. Identify base image and its size
  4. Count layers (each RUN/COPY/ADD = 1 layer)

  5. Check for common anti-patterns

  6. Apply optimization checklist

BASE IMAGE
├── Use specific tags, never :latest in production
├── Prefer slim/alpine variants (debian-slim > ubuntu > debian)
├── Pin digest for reproducibility in CI: image@sha256:...
└── Match base to runtime needs (don't use python:3.12 for a compiled binary)

LAYER OPTIMIZATION
├── Combine related RUN commands with && \
├── Order layers: least-changing first (deps before source code)
├── Clean package manager cache in the same RUN layer
├── Use .dockerignore to exclude unnecessary files
└── Separate build deps from runtime deps

BUILD CACHE
├── COPY dependency files before source code (package.json, requirements.txt, go.mod)
├── Install deps in a separate layer from code copy
├── Use BuildKit cache mounts: --mount=type=cache,target=/root/.cache
└── Avoid COPY . . before dependency installation

MULTI-STAGE BUILDS
├── Stage 1: build (full SDK, build tools, dev deps)
├── Stage 2: runtime (minimal base, only production artifacts)
├── COPY --from=builder only what's needed
└── Final image should have NO build tools, NO source code, NO dev deps
  1. Generate optimized Dockerfile
  2. Apply all relevant optimizations
  3. Add inline comments explaining each decision

  4. Report estimated size reduction

  5. Validate 

    python3 scripts/dockerfile_analyzer.py Dockerfile

/docker:compose — Docker Compose Configuration

  1. Identify services
  2. Application (web, API, worker)
  3. Database (postgres, mysql, redis, mongo)
  4. Cache (redis, memcached)
  5. Queue (rabbitmq, kafka)

  6. Reverse proxy (nginx, traefik, caddy)

  7. Apply compose best practices

SERVICES
├── Use depends_on with condition: service_healthy
├── Add healthchecks for every service
├── Set resource limits (mem_limit, cpus)
├── Use named volumes for persistent data
└── Pin image versions

NETWORKING
├── Create explicit networks (don't rely on default)
├── Separate frontend and backend networks
├── Only expose ports that need external access
└── Use internal: true for backend-only networks

ENVIRONMENT
├── Use env_file for secrets, not inline environment
├── Never commit .env files (add to .gitignore)
├── Use variable substitution: ${VAR:-default}
└── Document all required env vars

DEVELOPMENT vs PRODUCTION
├── Use compose profiles or override files
├── Dev: bind mounts for hot reload, debug ports exposed
├── Prod: named volumes, no debug ports, restart: unless-stopped
└── docker-compose.override.yml for dev-only config
  1. Generate compose file
  2. Output docker-compose.yml with healthchecks, networks, volumes
  3. Generate .env.example with all required variables documented
  4. Add dev/prod profile annotations

/docker:security — Container Security Audit

  1. Dockerfile audit
Check Severity Fix
Running as root Critical Add USER nonroot after creating user
Using :latest tag High Pin to specific version
Secrets in ENV/ARG Critical Use BuildKit secrets: --mount=type=secret
COPY with broad glob Medium Use specific paths, add .dockerignore
Unnecessary EXPOSE Low Only expose ports the app uses
No HEALTHCHECK Medium Add HEALTHCHECK with appropriate interval
Privileged instructions High Avoid --privileged, drop capabilities
Package manager cache retained Low Clean in same RUN layer
  1. Runtime security checks
Check Severity Fix
Container running as root Critical Set user in Dockerfile or compose
Writable root filesystem Medium Use read_only: true in compose
All capabilities retained High Drop all, add only needed: cap_drop: [ALL]
No resource limits Medium Set mem_limit and cpus
Host network mode High Use bridge or custom network
Sensitive mounts Critical Never mount /etc, /var/run/docker.sock in prod
No log driver configured Low Set logging: with size limits
  1. Generate security report 
    SECURITY AUDIT — [Dockerfile/Image name]
Date: [timestamp]

CRITICAL: [count]
HIGH:     [count]
MEDIUM:   [count]
LOW:      [count]

[Detailed findings with fix recommendations]

Tooling

scripts/dockerfile_analyzer.py

CLI utility for static analysis of Dockerfiles.

Features: - Layer count and optimization suggestions - Base image analysis with size estimates - Anti-pattern detection (15+ rules) - Security issue flagging - Multi-stage build detection and validation - JSON and text output

Usage: 

# Analyze a Dockerfile
python3 scripts/dockerfile_analyzer.py Dockerfile

# JSON output
python3 scripts/dockerfile_analyzer.py Dockerfile --output json

# Analyze with security focus
python3 scripts/dockerfile_analyzer.py Dockerfile --security

# Check a specific directory
python3 scripts/dockerfile_analyzer.py path/to/Dockerfile

scripts/compose_validator.py

CLI utility for validating docker-compose files.

Features: - Service dependency validation - Healthcheck presence detection - Network configuration analysis - Volume mount validation - Environment variable audit - Port conflict detection - Best practice scoring

Usage: 

# Validate a compose file
python3 scripts/compose_validator.py docker-compose.yml

# JSON output
python3 scripts/compose_validator.py docker-compose.yml --output json

# Strict mode (fail on warnings)
python3 scripts/compose_validator.py docker-compose.yml --strict

Multi-Stage Build Patterns

Pattern 1: Compiled Language (Go, Rust, C++)

# Build stage
FROM golang:1.22-alpine AS builder
WORKDIR /app
COPY go.mod go.sum ./
RUN go mod download
COPY . .
RUN CGO_ENABLED=0 go build -ldflags="-s -w" -o /app/server ./cmd/server

# Runtime stage
FROM gcr.io/distroless/static-debian12
COPY --from=builder /app/server /server
USER nonroot:nonroot
ENTRYPOINT ["/server"]

Pattern 2: Node.js / TypeScript

# Dependencies stage
FROM node:20-alpine AS deps
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci --production=false

# Build stage
FROM deps AS builder
COPY . .
RUN npm run build

# Runtime stage
FROM node:20-alpine
WORKDIR /app
RUN addgroup -g 1001 -S appgroup && adduser -S appuser -u 1001
COPY --from=builder /app/dist ./dist
COPY --from=deps /app/node_modules ./node_modules
COPY package.json ./
USER appuser
EXPOSE 3000
CMD ["node", "dist/index.js"]

Pattern 3: Python

# Build stage
FROM python:3.12-slim AS builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir --prefix=/install -r requirements.txt

# Runtime stage
FROM python:3.12-slim
WORKDIR /app
RUN groupadd -r appgroup && useradd -r -g appgroup appuser
COPY --from=builder /install /usr/local
COPY . .
USER appuser
EXPOSE 8000
CMD ["python", "-m", "uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

Base Image Decision Tree

Is it a compiled binary (Go, Rust, C)?
├── Yes → distroless/static or scratch
└── No
    ├── Need a shell for debugging?
    │   ├── Yes → alpine variant (e.g., node:20-alpine)
    │   └── No → distroless variant
    ├── Need glibc (not musl)?
    │   ├── Yes → slim variant (e.g., python:3.12-slim)
    │   └── No → alpine variant
    └── Need specific OS packages?
        ├── Many → debian-slim
        └── Few → alpine + apk add

Proactive Triggers

Flag these without being asked:

  • Dockerfile uses :latest → Suggest pinning to a specific version tag.
  • No .dockerignore → Create one. At minimum: .git, node_modules, __pycache__, .env.
  • COPY . . before dependency install → Cache bust. Reorder to install deps first.
  • Running as root → Add USER instruction. No exceptions for production.
  • Secrets in ENV or ARG → Use BuildKit secret mounts. Never bake secrets into layers.
  • Image over 1GB → Multi-stage build required. No reason for a production image this large.
  • No healthcheck → Add one. Orchestrators (Compose, K8s) need it for proper lifecycle management.
  • apt-get without cleanup in same layer → rm -rf /var/lib/apt/lists/* in the same RUN.

Installation

One-liner (any tool)

git clone https://github.com/alirezarezvani/claude-skills.git
cp -r claude-skills/engineering/docker-development ~/.claude/skills/

Multi-tool install

./scripts/convert.sh --skill docker-development --tool codex|gemini|cursor|windsurf|openclaw

OpenClaw

clawhub install cs-docker-development
  • senior-devops — Broader DevOps scope (CI/CD, IaC, monitoring). Complementary — use docker-development for container-specific work, senior-devops for pipeline and infrastructure.
  • senior-security — Application security. Complementary — docker-development covers container security, senior-security covers application-level threats.
  • autoresearch-agent — Can optimize Docker build times or image sizes as measurable experiments.
  • ci-cd-pipeline-builder — Pipeline construction. Complementary — docker-development builds the containers, ci-cd-pipeline-builder deploys them.