agentsclimarketplace

Devops mrgoonie

Skill jackspace/ClaudeSkillz/skills/devops_mrgoonie

ClaudeSkillz: For when you need skills, but lazier

Install
npx -y skills add jackspace/ClaudeSkillz --skill devops_mrgoonie

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 15 stars15 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native applications.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

8.1 KB, ~1.8k tokens by cl100k_base, as published. Nobody here has run it

DevOps Skill

Comprehensive guide for deploying and managing cloud infrastructure across Cloudflare edge platform, Docker containerization, and Google Cloud Platform.

When to Use This Skill

Use this skill when:

  • Deploying serverless applications to Cloudflare Workers
  • Containerizing applications with Docker
  • Managing Google Cloud infrastructure with gcloud CLI
  • Setting up CI/CD pipelines across platforms
  • Optimizing cloud infrastructure costs
  • Implementing multi-region deployments
  • Building edge-first architectures
  • Managing container orchestration with Kubernetes
  • Configuring cloud storage solutions (R2, Cloud Storage)
  • Automating infrastructure with scripts and IaC

Platform Selection Guide

When to Use Cloudflare

Best For:

  • Edge-first applications with global distribution
  • Ultra-low latency requirements (<50ms)
  • Static sites with serverless functions
  • Zero egress cost scenarios (R2 storage)
  • WebSocket/real-time applications (Durable Objects)
  • AI/ML at the edge (Workers AI)

Key Products:

  • Workers (serverless functions)
  • R2 (object storage, S3-compatible)
  • D1 (SQLite database with global replication)
  • KV (key-value store)
  • Pages (static hosting + functions)
  • Durable Objects (stateful compute)
  • Browser Rendering (headless browser automation)

Cost Profile: Pay-per-request, generous free tier, zero egress fees

When to Use Docker

Best For:

  • Local development consistency
  • Microservices architectures
  • Multi-language stack applications
  • Traditional VPS/VM deployments
  • Kubernetes orchestration
  • CI/CD build environments
  • Database containerization (dev/test)

Key Capabilities:

  • Application isolation and portability
  • Multi-stage builds for optimization
  • Docker Compose for multi-container apps
  • Volume management for data persistence
  • Network configuration and service discovery
  • Cross-platform compatibility (amd64, arm64)

Cost Profile: Infrastructure cost only (compute + storage)

When to Use Google Cloud

Best For:

  • Enterprise-scale applications
  • Data analytics and ML pipelines (BigQuery, Vertex AI)
  • Hybrid/multi-cloud deployments
  • Kubernetes at scale (GKE)
  • Managed databases (Cloud SQL, Firestore, Spanner)
  • Complex IAM and compliance requirements

Key Services:

  • Compute Engine (VMs)
  • GKE (managed Kubernetes)
  • Cloud Run (containerized serverless)
  • App Engine (PaaS)
  • Cloud Storage (object storage)
  • Cloud SQL (managed databases)

Cost Profile: Varied pricing, sustained use discounts, committed use contracts

Quick Start

Cloudflare Workers

# Install Wrangler CLI
npm install -g wrangler

# Create and deploy Worker
wrangler init my-worker
cd my-worker
wrangler deploy

See: references/cloudflare-workers-basics.md

Docker Container

# Create Dockerfile
cat > Dockerfile <<EOF
FROM node:20-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --production
COPY . .
EXPOSE 3000
CMD ["node", "server.js"]
EOF

# Build and run
docker build -t myapp .
docker run -p 3000:3000 myapp

See: references/docker-basics.md

Google Cloud Deployment

# Install and authenticate
curl https://sdk.cloud.google.com | bash
gcloud init
gcloud auth login

# Deploy to Cloud Run
gcloud run deploy my-service \
  --image gcr.io/project/image \
  --region us-central1

See: references/gcloud-platform.md

Reference Navigation

Cloudflare Platform

  • cloudflare-platform.md - Edge computing overview, key components
  • cloudflare-workers-basics.md - Getting started, handler types, basic patterns
  • cloudflare-workers-advanced.md - Advanced patterns, performance, optimization
  • cloudflare-workers-apis.md - Runtime APIs, bindings, integrations
  • cloudflare-r2-storage.md - R2 object storage, S3 compatibility, best practices
  • cloudflare-d1-kv.md - D1 SQLite database, KV store, use cases
  • browser-rendering.md - Puppeteer/Playwright automation on Cloudflare

Docker Containerization

  • docker-basics.md - Core concepts, Dockerfile, images, containers
  • docker-compose.md - Multi-container apps, networking, volumes

Google Cloud Platform

  • gcloud-platform.md - GCP overview, gcloud CLI, authentication
  • gcloud-services.md - Compute Engine, GKE, Cloud Run, App Engine

Python Utilities

  • scripts/cloudflare-deploy.py - Automate Cloudflare Worker deployments
  • scripts/docker-optimize.py - Analyze and optimize Dockerfiles

Common Workflows

Edge + Container Hybrid

# Cloudflare Workers (API Gateway)
# -> Docker containers on Cloud Run (Backend Services)
# -> R2 (Object Storage)

# Benefits:
# - Edge caching and routing
# - Containerized business logic
# - Global distribution

Multi-Stage Docker Build

# Build stage
FROM node:20-alpine AS build
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

# Production stage
FROM node:20-alpine
WORKDIR /app
COPY --from=build /app/dist ./dist
COPY --from=build /app/node_modules ./node_modules
USER node
CMD ["node", "dist/server.js"]

CI/CD Pipeline Pattern

# 1. Build: Docker multi-stage build
# 2. Test: Run tests in container
# 3. Push: Push to registry (GCR, Docker Hub)
# 4. Deploy: Deploy to Cloudflare Workers / Cloud Run
# 5. Verify: Health checks and smoke tests

Best Practices

Security

  • Run containers as non-root user
  • Use service account impersonation (GCP)
  • Store secrets in environment variables, not code
  • Scan images for vulnerabilities (Docker Scout)
  • Use API tokens with minimal permissions

Performance

  • Multi-stage Docker builds to reduce image size
  • Edge caching with Cloudflare KV
  • Use R2 for zero egress cost storage
  • Implement health checks for containers
  • Set appropriate timeouts and resource limits

Cost Optimization

  • Use Cloudflare R2 instead of S3 for large egress
  • Implement caching strategies (edge + KV)
  • Right-size container resources
  • Use sustained use discounts (GCP)
  • Monitor usage with cloud provider dashboards

Development

  • Use Docker Compose for local development
  • Wrangler dev for local Worker testing
  • Named gcloud configurations for multi-environment
  • Version control infrastructure code
  • Implement automated testing in CI/CD

Decision Matrix

NeedChoose
Sub-50ms latency globallyCloudflare Workers
Large file storage (zero egress)Cloudflare R2
SQL database (global reads)Cloudflare D1
Containerized workloadsDocker + Cloud Run/GKE
Enterprise KubernetesGKE
Managed relational DBCloud SQL
Static site + APICloudflare Pages
WebSocket/real-timeCloudflare Durable Objects
ML/AI pipelinesGCP Vertex AI
Browser automationCloudflare Browser Rendering

Resources

Implementation Checklist

Cloudflare Workers

  • Install Wrangler CLI
  • Create Worker project
  • Configure wrangler.toml (bindings, routes)
  • Test locally with wrangler dev
  • Deploy with wrangler deploy

Docker

  • Write Dockerfile with multi-stage builds
  • Create .dockerignore file
  • Test build locally
  • Push to registry
  • Deploy to target platform

Google Cloud

  • Install gcloud CLI
  • Authenticate with service account
  • Create project and enable APIs
  • Configure IAM permissions
  • Deploy and monitor resources

What ships with it: 2 files

11.3 KB alongside SKILL.md

Gives 2 of the 12 instructions most containers cloud skills give in ~1.8k tokens

Counted across 607 of the 657 authors here whose files we hold, read 2026-08-07

  • Run containers as a non-root userhere, and in 66 of 607, across 46 files
  • Use multi-stage buildshere, and in 53 of 607, across 44 files
  • Use Promise.all for independent operationsin 47 of 607, across 13 files
  • Import directly instead of barrel filesin 46 of 607, across 12 files
  • Use ternary instead of AND for conditionalsin 45 of 607, across 12 files
  • Use Set or Map for O(1) lookupsin 42 of 607, across 10 files
  • Create a .dockerignore filein 41 of 607, across 31 files
  • Read individual rule files for detailsin 39 of 607, across 9 files
  • Copy dependency files before source codein 36 of 607, across 23 files
  • Authenticate server actions like API routesin 35 of 607, across 7 files
  • Use next/dynamic for heavy componentsin 34 of 607, across 9 files
  • Use React.cache for per-request deduplicationin 34 of 607, across 10 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 327,069. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.