agent-launcher-orchest…
Use when someone wants to build, launch, grade or schedule a Claude Managed Agent in their own Anthropic account ('build me an…
Set up CI/CD pipelines, infrastructure as code, containers and deployments on AWS, GCP or Azure. Use whenever the user needs a build or deploy pipeline, Terraform, a Dockerfile, or wants to manage a release to the cloud.
Claude Code
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Codex
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Cursor
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Gemini CLI
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GitHub Copilot
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OpenCode
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Windsurf
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name: "senior-devops" description: "Set up CI/CD pipelines, infrastructure as code, containers and deployments on AWS, GCP or Azure. Use whenever the user needs a build or deploy pipeline, Terraform, a Dockerfile, or wants to manage a release to the cloud."
Complete toolkit for senior devops with modern tools and best practices.
This skill provides three core capabilities through automated scripts:
# Script 1: Pipeline Generator — scaffolds CI/CD pipelines for GitHub Actions or CircleCI python scripts/pipeline_generator.py ./app --platform=github --stages=build,test,deploy # Script 2: Terraform Scaffolder — generates and validates IaC modules for AWS/GCP/Azure python scripts/terraform_scaffolder.py ./infra --provider=aws --module=ecs-service --verbose # Script 3: Deployment Manager — generates deployment manifests + runbooks with rollback support python3 scripts/deployment_manager.py deploy --env=staging --image=app:1.2.3 --strategy=blue-green --verbose --json
Scaffolds CI/CD pipeline configurations for GitHub Actions or CircleCI, with stages for build, test, security scan, and deploy.
**Example — GitHub Actions workflow:**
# .github/workflows/ci.yml
name: CI/CD Pipeline
on:
push:
branches: [main, develop]
pull_request:
branches: [main]
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Set up Node.js
uses: actions/setup-node@v4
with:
node-version: '20'
cache: 'npm'
- run: npm ci
- run: npm run lint
- run: npm test -- --coverage
- name: Upload coverage
uses: codecov/codecov-action@v4
build-docker:
needs: build-and-test
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Build and push image
uses: docker/build-push-action@v5
with:
push: ${{ github.ref == 'refs/heads/main' }}
tags: ghcr.io/${{ github.repository }}:${{ github.sha }}
deploy:
needs: build-docker
if: github.ref == 'refs/heads/main'
runs-on: ubuntu-latest
steps:
- name: Deploy to ECS
run: |
aws ecs update-service \
--cluster production \
--service app-service \
--force-new-deployment**Usage:**
python scripts/pipeline_generator.py <project-path> --platform=github|circleci --stages=build,test,deploy
Generates, validates, and plans Terraform modules. Enforces consistent module structure and runs `terraform validate` + `terraform plan` before any apply.
**Example — AWS ECS service module:**
# modules/ecs-service/main.tf
resource "aws_ecs_task_definition" "app" {
family = var.service_name
requires_compatibilities = ["FARGATE"]
network_mode = "awsvpc"
cpu = var.cpu
memory = var.memory
container_definitions = jsonencode([{
name = var.service_name
image = var.container_image
essential = true
portMappings = [{
containerPort = var.container_port
protocol = "tcp"
}]
environment = [for k, v in var.env_vars : { name = k, value = v }]
logConfiguration = {
logDriver = "awslogs"
options = {
awslogs-group = "/ecs/${var.service_name}"
awslogs-region = var.aws_region
awslogs-stream-prefix = "ecs"
}
}
}])
}
resource "aws_ecs_service" "app" {
name = var.service_name
cluster = var.cluster_id
task_definition = aws_ecs_task_definition.app.arn
desired_count = var.desired_count
launch_type = "FARGATE"
network_configuration {
subnets = var.private_subnet_ids
security_groups = [aws_security_group.app.id]
assign_public_ip = false
}
load_balancer {
target_group_arn = aws_lb_target_group.app.arn
container_name = var.service_name
container_port = var.container_port
}
}**Usage:**
python scripts/terraform_scaffolder.py <target-path> --provider=aws|gcp|azure --module=ecs-service|gke-deployment|aks-service [--verbose]
Generates Kubernetes deployment manifests and ordered kubectl runbooks for blue/green or rolling strategies, with health-check gates before traffic switches and rollback runbooks. The tool writes manifests and prints the commands — it never applies them to a cluster itself, so every change gets a human review.
**Example — Kubernetes blue/green deployment (blue-slot specific elements):**
# k8s/deployment-blue.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: app-blue
labels:
app: myapp
slot: blue # slot label distinguishes blue from green
spec:
replicas: 3
selector:
matchLabels:
app: myapp
slot: blue
template:
metadata:
labels:
app: myapp
slot: blue
spec:
containers:
- name: app
image: ghcr.io/org/app:1.2.3
readinessProbe: # gate: pod must pass before traffic switches
httpGet:
path: /healthz
port: 8080
initialDelaySeconds: 10
periodSeconds: 5
resources:
requests:
cpu: "250m"
memory: "256Mi"
limits:
cpu: "500m"
memory: "512Mi"**Usage:**
python scripts/deployment_manager.py deploy \ --env=staging|production \ --image=app:1.2.3 \ --strategy=blue-green|rolling \ --health-check-url=https://app.example.com/healthz python scripts/deployment_manager.py rollback --env=production --to-version=1.2.2 python scripts/deployment_manager.py --analyze --env=production # audit current state
411 production-ready skills for Claude Code and 12 other coding agents, covering engineering, product, marketing, compliance, finance and the C-suite. We test whether each skill loads when you ask in plain words, and publish the results.
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