Agent skill

Deployment Pipeline Design

by HermeticOrmus in HermeticOrmus/LibreUIUX-Claude-Code

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration.

MITAuto-check passedDevOps & Cloud

Install Deployment Pipeline Design

skills CLI
$ npx skills add HermeticOrmus/LibreUIUX-Claude-Code --skill deployment-pipeline-design -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install HermeticOrmus/LibreUIUX-Claude-Code deployment-pipeline-design --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/HermeticOrmus/LibreUIUX-Claude-Code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/cicd-automation/skills/deployment-pipeline-design .claude/skills/deployment-pipeline-design && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
deployment-pipeline-design
GitHub stars
112
Used in
11 other repos
Token cost
~2.1k tokens
SKILL.md length
346 words
Files
1
Skills in repo
15
Repo updated
First seen
Licence
MIT

At a glance

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration.

  • Works in 4 steps: Rolling Deployment → Blue-Green Deployment → Canary Deployment → …
  • Architecting deployment workflows
  • SKILL.md covers Purpose, When to Use, Pipeline Stages and Approval Gate Patterns, plus 7 more sections
  • Calls kubectl; needs API_KEY

What it does

Deployment Pipeline Design is an agent skill from HermeticOrmus/LibreUIUX-Claude-Code. Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering CI/CD and Deployment. The repository describes itself as: UI/UX system for Claude Code: 71 plugins, 93 agents, 74 skills. Design mastery, archetypal design, accessibility, and frontend workflows in one validated plugin marketplace. The licence is MIT.

When your agent uses it

  • Architecting deployment workflows
  • Setting up continuous delivery
  • Implementing GitOps practices

Example prompts

  • “/deployment-pipeline-design”

Requirements

  • Python 3
  • Docker
  • A credential in API_KEY

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Rolling Deployment
  2. Blue-Green Deployment
  3. Canary Deployment
  4. Feature Flags

What it can do on your machine

Read from SKILL.md and the folder at commit 41a968c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • kubectl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use kubectl, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Deployment Pipeline Design loads about 2.1k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 346 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~60
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from HermeticOrmus/LibreUIUX-Claude-Code at commit 41a968c, republished under its MIT licence (© HermeticOrmus). 346 words, ~2,057 tokens.

Download SKILL.mdSave it as .claude/skills/deployment-pipeline-design/SKILL.md (or your agent's skills folder).
name
deployment-pipeline-design
description
Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.

Deployment Pipeline Design

Architecture patterns for multi-stage CI/CD pipelines with approval gates and deployment strategies.

Purpose

Design robust, secure deployment pipelines that balance speed with safety through proper stage organization and approval workflows.

When to Use

  • Design CI/CD architecture
  • Implement deployment gates
  • Configure multi-environment pipelines
  • Establish deployment best practices
  • Implement progressive delivery

Pipeline Stages

Standard Pipeline Flow
┌─────────┐   ┌──────┐   ┌─────────┐   ┌────────┐   ┌──────────┐
│  Build  │ → │ Test │ → │ Staging │ → │ Approve│ → │Production│
└─────────┘   └──────┘   └─────────┘   └────────┘   └──────────┘
Detailed Stage Breakdown
  1. Source - Code checkout
  2. Build - Compile, package, containerize
  3. Test - Unit, integration, security scans
  4. Staging Deploy - Deploy to staging environment
  5. Integration Tests - E2E, smoke tests
  6. Approval Gate - Manual approval required
  7. Production Deploy - Canary, blue-green, rolling
  8. Verification - Health checks, monitoring
  9. Rollback - Automated rollback on failure

Approval Gate Patterns

Pattern 1: Manual Approval
yaml
# GitHub Actions
production-deploy:
  needs: staging-deploy
  environment:
    name: production
    url: https://app.example.com
  runs-on: ubuntu-latest
  steps:
    - name: Deploy to production
      run: |
        # Deployment commands
Pattern 2: Time-Based Approval
yaml
# GitLab CI
deploy:production:
  stage: deploy
  script:
    - deploy.sh production
  environment:
    name: production
  when: delayed
  start_in: 30 minutes
  only:
    - main
Pattern 3: Multi-Approver
yaml
# Azure Pipelines
stages:
- stage: Production
  dependsOn: Staging
  jobs:
  - deployment: Deploy
    environment:
      name: production
      resourceType: Kubernetes
    strategy:
      runOnce:
        preDeploy:
          steps:
          - task: ManualValidation@0
            inputs:
              notifyUsers: 'team-leads@example.com'
              instructions: 'Review staging metrics before approving'

Reference: See assets/approval-gate-template.yml

Deployment Strategies

1. Rolling Deployment
yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
spec:
  replicas: 10
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 2
      maxUnavailable: 1

Characteristics:

  • Gradual rollout
  • Zero downtime
  • Easy rollback
  • Best for most applications
2. Blue-Green Deployment
yaml
# Blue (current)
kubectl apply -f blue-deployment.yaml
kubectl label service my-app version=blue

# Green (new)
kubectl apply -f green-deployment.yaml
# Test green environment
kubectl label service my-app version=green

# Rollback if needed
kubectl label service my-app version=blue

Characteristics:

  • Instant switchover
  • Easy rollback
  • Doubles infrastructure cost temporarily
  • Good for high-risk deployments
3. Canary Deployment
yaml
apiVersion: argoproj.io/v1alpha1
kind: Rollout
metadata:
  name: my-app
spec:
  replicas: 10
  strategy:
    canary:
      steps:
      - setWeight: 10
      - pause: {duration: 5m}
      - setWeight: 25
      - pause: {duration: 5m}
      - setWeight: 50
      - pause: {duration: 5m}
      - setWeight: 100

Characteristics:

  • Gradual traffic shift
  • Risk mitigation
  • Real user testing
  • Requires service mesh or similar
4. Feature Flags
python
from flagsmith import Flagsmith

flagsmith = Flagsmith(environment_key="API_KEY")

if flagsmith.has_feature("new_checkout_flow"):
    # New code path
    process_checkout_v2()
else:
    # Existing code path
    process_checkout_v1()

Characteristics:

  • Deploy without releasing
  • A/B testing
  • Instant rollback
  • Granular control

Pipeline Orchestration

Multi-Stage Pipeline Example
yaml
name: Production Pipeline

on:
  push:
    branches: [ main ]

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Build application
        run: make build
      - name: Build Docker image
        run: docker build -t myapp:${{ github.sha }} .
      - name: Push to registry
        run: docker push myapp:${{ github.sha }}

  test:
    needs: build
    runs-on: ubuntu-latest
    steps:
      - name: Unit tests
        run: make test
      - name: Security scan
        run: trivy image myapp:${{ github.sha }}

  deploy-staging:
    needs: test
    runs-on: ubuntu-latest
    environment:
      name: staging
    steps:
      - name: Deploy to staging
        run: kubectl apply -f k8s/staging/

  integration-test:
    needs: deploy-staging
    runs-on: ubuntu-latest
    steps:
      - name: Run E2E tests
        run: npm run test:e2e

  deploy-production:
    needs: integration-test
    runs-on: ubuntu-latest
    environment:
      name: production
    steps:
      - name: Canary deployment
        run: |
          kubectl apply -f k8s/production/
          kubectl argo rollouts promote my-app

  verify:
    needs: deploy-production
    runs-on: ubuntu-latest
    steps:
      - name: Health check
        run: curl -f https://app.example.com/health
      - name: Notify team
        run: |
          curl -X POST ${{ secrets.SLACK_WEBHOOK }} \
            -d '{"text":"Production deployment successful!"}'

Pipeline Best Practices

  1. Fail fast - Run quick tests first
  2. Parallel execution - Run independent jobs concurrently
  3. Caching - Cache dependencies between runs
  4. Artifact management - Store build artifacts
  5. Environment parity - Keep environments consistent
  6. Secrets management - Use secret stores (Vault, etc.)
  7. Deployment windows - Schedule deployments appropriately
  8. Monitoring integration - Track deployment metrics
  9. Rollback automation - Auto-rollback on failures
  10. Documentation - Document pipeline stages

Rollback Strategies

Automated Rollback
yaml
deploy-and-verify:
  steps:
    - name: Deploy new version
      run: kubectl apply -f k8s/

    - name: Wait for rollout
      run: kubectl rollout status deployment/my-app

    - name: Health check
      id: health
      run: |
        for i in {1..10}; do
          if curl -sf https://app.example.com/health; then
            exit 0
          fi
          sleep 10
        done
        exit 1

    - name: Rollback on failure
      if: failure()
      run: kubectl rollout undo deployment/my-app
Manual Rollback
bash
# List revision history
kubectl rollout history deployment/my-app

# Rollback to previous version
kubectl rollout undo deployment/my-app

# Rollback to specific revision
kubectl rollout undo deployment/my-app --to-revision=3

Monitoring and Metrics

Key Pipeline Metrics
  • Deployment Frequency - How often deployments occur
  • Lead Time - Time from commit to production
  • Change Failure Rate - Percentage of failed deployments
  • Mean Time to Recovery (MTTR) - Time to recover from failure
  • Pipeline Success Rate - Percentage of successful runs
  • Average Pipeline Duration - Time to complete pipeline
Integration with Monitoring
yaml
- name: Post-deployment verification
  run: |
    # Wait for metrics stabilization
    sleep 60

    # Check error rate
    ERROR_RATE=$(curl -s "$PROMETHEUS_URL/api/v1/query?query=rate(http_errors_total[5m])" | jq '.data.result[0].value[1]')

    if (( $(echo "$ERROR_RATE > 0.01" | bc -l) )); then
      echo "Error rate too high: $ERROR_RATE"
      exit 1
    fi

Reference Files

  • references/pipeline-orchestration.md - Complex pipeline patterns
  • assets/approval-gate-template.yml - Approval workflow templates
  • github-actions-templates - For GitHub Actions implementation
  • gitlab-ci-patterns - For GitLab CI implementation
  • secrets-management - For secrets handling

© HermeticOrmus, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/cicd-automation/skills/deployment-pipeline-design of HermeticOrmus/LibreUIUX-Claude-Code.

Open the folder on GitHubat commit 41a968c

Used in 11 other repositories

We found 37 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 11 other GitHub owners. This page covers the copy in HermeticOrmus/LibreUIUX-Claude-Code, which our catalogue first saw on October 7, 2026.

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Categories

Questions about Deployment Pipeline Design

What does Deployment Pipeline Design do?

Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Deployment Pipeline Design is an agent skill from HermeticOrmus/LibreUIUX-Claude-Code. Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration.

When should I use Deployment Pipeline Design?

Deployment Pipeline Design fits situations like: architecting deployment workflows; setting up continuous delivery; implementing GitOps practices.

How do I install Deployment Pipeline Design in Claude Code?

Run `npx skills add HermeticOrmus/LibreUIUX-Claude-Code --skill deployment-pipeline-design -a claude-code`. Or copy the skill folder (plugins/cicd-automation/skills/deployment-pipeline-design in HermeticOrmus/LibreUIUX-Claude-Code) into .claude/skills/deployment-pipeline-design in your project. Claude Code loads it when a task matches its description.

How do I install Deployment Pipeline Design in Codex?

Run `npx skills add HermeticOrmus/LibreUIUX-Claude-Code --skill deployment-pipeline-design -a codex`. Or copy the skill folder (plugins/cicd-automation/skills/deployment-pipeline-design in HermeticOrmus/LibreUIUX-Claude-Code) into .agents/skills/deployment-pipeline-design in your project. Codex loads it when a task matches its description.

Can I use Deployment Pipeline Design in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add HermeticOrmus/LibreUIUX-Claude-Code --skill deployment-pipeline-design -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deployment-pipeline-design, .gemini/skills/deployment-pipeline-design, .github/skills/deployment-pipeline-design and .opencode/skills/deployment-pipeline-design in your project.

What does Deployment Pipeline Design need to run?

Going by SKILL.md and its folder, Deployment Pipeline Design needs the command-line tools its instructions call (kubectl) and credentials named API_KEY. Our summary lists: Python 3; Docker; A credential in API_KEY.

Does Deployment Pipeline Design access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Deployment Pipeline Design safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Deployment Pipeline Design use?

Deployment Pipeline Design is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Deployment Pipeline Design use?

About 2.1k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Deployment Pipeline Design?

Skills that share tags, products or a category with Deployment Pipeline Design: Senior DevOps Toolkit (maslennikov-ig/claude-code-orchestrator-kit, 260 stars), AI News Radar (LearnPrompt/ai-news-radar, 1.8k stars), Use Vercel Action (amondnet/vercel-action, 764 stars) and CI CD And Automation (dzhalaevd/Donatello, 135 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Deployment Pipeline Design?

HermeticOrmus (a GitHub user) maintains it in HermeticOrmus/LibreUIUX-Claude-Code, which has 112 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 4, 2026.

Source: HermeticOrmus/LibreUIUX-Claude-Code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.