From coreweave-pack
Integrates CoreWeave deployments into CI/CD pipelines using GitHub Actions. Automates container builds, inference service deployments, and GPU manifest validation in pull requests.
How this skill is triggered — by the user, by Claude, or both
Slash command
/coreweave-pack:coreweave-ci-integrationThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
```yaml
name: CoreWeave Deploy
on:
push:
branches: [main]
paths: ["k8s/**", "Dockerfile"]
jobs:
build-deploy:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Build and push container
run: |
echo "${{ secrets.GHCR_TOKEN }}" | docker login ghcr.io -u ${{ github.actor }} --password-stdin
docker build -t ghcr.io/${{ github.repository }}/inference:${{ github.sha }} .
docker push ghcr.io/${{ github.repository }}/inference:${{ github.sha }}
- name: Deploy to CoreWeave
env:
KUBECONFIG_DATA: ${{ secrets.COREWEAVE_KUBECONFIG }}
run: |
echo "$KUBECONFIG_DATA" | base64 -d > /tmp/kubeconfig
export KUBECONFIG=/tmp/kubeconfig
kubectl set image deployment/inference \
inference=ghcr.io/${{ github.repository }}/inference:${{ github.sha }}
kubectl rollout status deployment/inference --timeout=300s
- name: Validate deployment
run: |
export KUBECONFIG=/tmp/kubeconfig
kubectl get pods -l app=inference
# Store secrets
gh secret set COREWEAVE_KUBECONFIG --body "$(base64 -w0 ~/.kube/coreweave)"
gh secret set GHCR_TOKEN --body "$GITHUB_TOKEN"
For deployment patterns, see coreweave-deploy-integration.
npx claudepluginhub ia23a-lachnita/claude-code-plugins-plus-fix-skills --plugin coreweave-pack2plugins reuse this skill
First indexed Jul 17, 2026
Integrate CoreWeave deployments into CI/CD pipelines with GitHub Actions. Use when automating container builds, deploying inference services from CI, or validating GPU manifests in pull requests. Trigger with phrases like "coreweave CI", "coreweave github actions", "coreweave pipeline", "automate coreweave deploy".
Guides collaborative design exploration before implementation: explores context, asks clarifying questions, proposes approaches, and writes a design doc for user approval.
Creates structured, bite-sized implementation plans from specs or requirements before writing code. Useful for breaking down multi-step tasks into testable steps with file structure and task boundaries.