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name: devops-infrastructure description: | Automatically reviews and optimizes Dockerfiles, CI/CD pipelines, and Infrastructure-as-Code.

Activates when you mention: Docker optimization, Dockerfile review, CI/CD pipeline, GitHub Actions, infrastructure code, Terraform, container security, deployment strategy.

Provides: Dockerfile multi-stage optimizations, CI/CD efficiency improvements, IaC best practices, security hardening, resource optimization.

Supports: Docker, docker-compose, GitHub Actions, Terraform, Kubernetes allowed-tools: ["Read", "Bash(docker images)", "Bash(docker ps)"]

DevOps & Infrastructure Skill

Automatically optimizes Docker configurations, CI/CD pipelines, and infrastructure code.

When This Skill Activates

Claude invokes this skill when you:

1. Show a Dockerfile or docker-compose.yml
2. Ask about CI/CD optimization
3. Mention container security
4. Discuss deployment strategies
5. Work with infrastructure code

What This Skill Does

1. Dockerfile Optimization

Checks for:

• Multi-stage builds
• Minimal base images (alpine/slim)
• Layer caching optimization
• Security (non-root user, specific versions)
• Image size reduction
• Build speed improvements

Example Optimization:

Copy# Before: 995MB
FROM python:3.11
COPY . /app
RUN pip install -r requirements.txt

# After: 145MB (85% reduction)
FROM python:3.11-slim AS builder
COPY requirements.txt .
RUN pip install --user --no-cache-dir -r requirements.txt

FROM python:3.11-slim
COPY --from=builder /root/.local /root/.local
COPY . /app
USER appuser:1001

2. CI/CD Pipeline Optimization

Checks for:

• Dependency caching
• Parallel job execution
• Matrix strategies
• Secrets management
• Permissions (least privilege)
• Security scanning integration

3. Container Security

Checks for:

• Running as root
• Exposed secrets
• Vulnerable base images
• Missing health checks
• Resource limits
• Network security

4. Infrastructure-as-Code Review

Supports:

• Terraform
• CloudFormation
• Kubernetes manifests
• docker-compose files

Archetype-Specific Optimizations

For rag-project:

• Optimize OpenSearch JVM settings
• Ollama model caching
• Redis connection pooling
• Multi-stage build for Python dependencies

For api-service:

• Separate worker and API images
• Celery resource optimization
• Database connection pooling
• Health check configuration

For frontend:

• Next.js standalone output
• Static asset optimization
• Build caching strategies
• Environment variable handling

Output Format

Provides:

1. Current Issues: Problems identified
2. Optimized Configuration: Improved version
3. Improvements: Size/speed/security gains
4. Migration Steps: How to apply changes
5. Testing: Verification steps

Example Usage

CopyUser: "Review my Dockerfile for production"
Claude: [Activates devops-infrastructure skill]
- Identifies single-stage build (large image)
- Suggests multi-stage optimization
- Adds security hardening
- Provides optimized Dockerfile

Result: 995MB → 145MB (85% reduction)