Agent skill

vastai-ci-integration

Configure Vast.ai CI/CD integration with GitHub Actions and automated GPU testing. Use when setting up automated testing on GPU instances, or integrating Vast.ai provisioning into CI/CD pipelines. Trigger with phrases like "vastai CI", "vastai github actions", "vastai automated testing", "vastai pipeline". '

intentsolutions.io2,596★ · 1 repos on radarProfile →
claude-codecan modify filesMIT
Install
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill vastai-ci-integration --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 6 KB
Bundled scripts: none
Version: 1.11.0
Declared author: Jeremy Longshore <jeremy@intentsolutions.io>
Allowed tools: ReadWriteEditBash(vastai:*)Grep
Requires: Designed for Claude Code, also compatible with Codex and OpenClaw
Path: skills/.curated/vastai-ci-integration/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,630
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Vast.ai CI Integration ## Overview Integrate Vast.ai GPU provisioning into CI/CD pipelines. Run GPU-accelerated tests, model validation, and benchmarks as part of your automated workflow using GitHub Actions with the Vast.ai CLI. ## Prerequisites - GitHub repository with Actions enabled - `VASTAI_API_KEY` stored as GitHub Actions secret - Docker image for GPU workload published to a registry ## Instructions ### Step 1: GitHub Actions Workflow ```yaml # .github/workflows/gpu-test.yml name: GPU Tests on: push: branches: [main] pull_request: jobs: gpu-test: runs-on: ubuntu-latest timeout-minutes: 30 steps: - uses: actions/checkout@v4 - name: Install Vast.ai CLI run: | pip install vastai vastai set api-key ${{ secrets.VASTAI_API_KEY }} - name: Provision GPU Instance id: provision run: | # Search for cheapest reliable GPU OFFER_ID=$(vastai search offers \ 'num_gpus=1 gpu_ram>=8 reliability>0.95 dph_total<=0.25' \ --order dph_total --raw --limit 1 \ | python3 -c "import sys,json; print(json.load(sys.stdin)[0]['id'])") # Create instance INSTANCE_ID=$(vastai create instance $OFFER_ID \ --image ghcr.io/${{ github.repository }}/gpu-test:latest \ --disk 20 --raw \ | python3 -c "import sys,j

What's inside
Steps it walks through
  1. Overview
  2. Prerequisites
  3. Instructions
  4. Step 1: GitHub Actions Workflow
  5. Step 2: Cost-Controlled CI
  6. Step 3: Mock Mode for Non-GPU CI
  7. Output
  8. Error Handling
  9. Resources
  10. Next Steps
  11. Examples
More from claude-code-plugins-plus-skills
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About this skill
What does the vastai-ci-integration skill do?

Configure Vast.ai CI/CD integration with GitHub Actions and automated GPU testing. Use when setting up automated testing on GPU instances, or integrating Vast.ai provisioning into CI/CD pipelines. Trigger with phrases like "vastai CI", "vastai github actions", "vastai automated testing", "vastai pipeline". '

How do I install it?

Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill vastai-ci-integration --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,630 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going