deploy
Deploy the application or manage infrastructure. Handles Docker builds, CI/CD, and deployment workflows.
Best use case
deploy is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Deploy the application or manage infrastructure. Handles Docker builds, CI/CD, and deployment workflows.
Teams using deploy should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/deploy/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How deploy Compares
| Feature / Agent | deploy | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Deploy the application or manage infrastructure. Handles Docker builds, CI/CD, and deployment workflows.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Deploy Execute the following deployment/infrastructure task: $ARGUMENTS ## Pre-deployment Checklist 1. **Verify build**: `pnpm build` 2. **Run tests**: `pnpm test` 3. **Check lint**: `pnpm lint` 4. **Review environment**: Verify .env configuration ## Docker Deployment ```bash # Build and start all services docker-compose up --build # Build specific service docker-compose build [service-name] # View logs docker-compose logs -f [service-name] ``` ## Environment Variables Required variables (see .template.env): - `GOOGLE_CLOUD_PROJECT` / `GOOGLE_API_KEY` — AI provider credentials - `LANGSMITH_API_KEY` — Observability (optional) - `PORT` — Backend server port (default: 3000) ## Post-deployment Verification 1. Health check: `curl http://localhost:3000/health` 2. Agent types: `curl http://localhost:3000/chat/agent-types` 3. Test chat: Send a test message through the UI or API
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