Production-ready GitHub Actions workflow patterns for testing, building, and deploying applications.
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AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongithub-actions-templatesExecute the skills CLI command in your project's root directory to begin installation:
Fetches github-actions-templates from sickn33/antigravity-awesome-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate github-actions-templates. Access via /github-actions-templates in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Production-ready GitHub Actions workflow patterns for testing, building, and deploying applications.
resources/implementation-playbook.md.Create efficient, secure GitHub Actions workflows for continuous integration and deployment across various tech stacks.
name: Test
on:
push:
branches: [ main, develop ]
pull_request:
branches: [ main ]
jobs:
test:
runs-on: ubuntu-latest
strategy:
matrix:
node-version: [18.x, 20.x]
steps:
- uses: actions/checkout@v4
- name: Use Node.js ${{ matrix.node-version }}
uses: actions/setup-node@v4
with:
node-version: ${{ matrix.node-version }}
cache: 'npm'
- name: Install dependencies
run: npm ci
- name: Run linter
run: npm run lint
- name: Run tests
run: npm test
- name: Upload coverage
uses: codecov/codecov-action@v3
with:
files: ./coverage/lcov.info
Reference: See assets/test-workflow.yml
name: Build and Push
on:
push:
branches: [ main ]
tags: [ 'v*' ]
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}
jobs:
build:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
steps:
- uses: actions/checkout@v4
- name: Log in to Container Registry
uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
type=ref,event=branch
type=ref,event=pr
type=semver,pattern={{version}}
type=semver,pattern={{major}}.{{minor}}
- name: Build and push
uses: docker/build-push-action@v5
with:
context: .
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max
Reference: See assets/deploy-workflow.yml
name: Deploy to Kubernetes
on:
push:
branches: [ main ]
jobs:
deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Configure AWS credentials
uses: aws-actions/configure-aws-credentials@v4
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-west-2
- name: Update kubeconfig
run: |
aws eks update-kubeconfig --name production-cluster --region us-west-2
- name: Deploy to Kubernetes
run: |
kubectl apply -f k8s/
kubectl rollout status deployment/my-app -n production
kubectl get services -n production
- name: Verify deployment
run: |
kubectl get pods -n production
kubectl describe deployment my-app -n production
name: Matrix Build
on: [push, pull_request]
jobs:
build:
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
python-version: ['3.9', '3.10', '3.11', '3.12']
steps:
- uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
- name: Run tests
run: pytest
Reference: See assets/matrix-build.yml
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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parcadei/continuous-claude-v3
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ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Keeps context tight: github-actions-templates is the kind of skill you can hand to a new teammate without a long onboarding doc.
github-actions-templates is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
github-actions-templates is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: github-actions-templates is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in github-actions-templates — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
github-actions-templates has been reliable in day-to-day use. Documentation quality is above average for community skills.
github-actions-templates reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for github-actions-templates matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: github-actions-templates is focused, and the summary matches what you get after install.
I recommend github-actions-templates for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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