setup-deploy

Overview of setup-deploy skill

setup-deploy is a deployment-setup skill for gstack that configures a project’s deploy metadata so future land-and-deploy runs can work automatically. It is best for agents or developers who need to turn a rough “how do we deploy this?” request into a repeatable deployment configuration, especially when the target platform is not yet pinned down.

The main job of the setup-deploy skill is practical discovery: identify the deployment provider, production URL, health check endpoint, and deploy status command, then write that configuration into CLAUDE.md. That makes it more useful than a generic prompt because it is meant to persist decisions instead of re-asking them every time.

Best fit for deployment setup work

Use setup-deploy when you already know the app should be deployable but need the deployment path clarified and recorded. It is a good fit for Fly.io, Render, Vercel, Netlify, Heroku, GitHub Actions, or a custom deployment flow.

What makes it different

The skill is oriented around configuration capture, not just advice. Its value is that it maps deployment choices into project memory so later automation has the right context. That matters when a repo has multiple environments, unclear status checks, or a deployment target that must be inferred from existing files.

When not to use it

If you only want a one-off explanation of how to deploy a sample app, a normal prompt may be enough. If the project already has a complete, stable deployment spec and no configuration needs to be written back, setup-deploy may add little beyond structured discovery.

How to Use setup-deploy skill

Install the skill in the right project context

Install with the repository’s skill command, then run it from the project where deployment settings should be recorded. A typical setup-deploy install flow is:

npx skills add garrytan/gstack --skill setup-deploy

After installation, make sure the agent is operating in the app repo whose CLAUDE.md should be updated, not in the skill repository itself.

Give it deployment facts, not just a goal

The setup-deploy usage pattern works best when your prompt includes the app type, current hosting target, and anything already known about release and health checks. Strong input looks like:

• “Set up deployment for a Node API on Render; production URL is https://api.example.com; health endpoint is /health; status command is curl -f.”
• “Configure deploy for a Next.js app on Vercel; use the main branch; document the deploy check command already used in CI.”

Weak input like “help me deploy this” forces the skill to infer too much and slows down the setup.

Read the skill files in this order

Start with SKILL.md to understand the action flow, then inspect SKILL.md.tmpl if you need to see how the generated skill is assembled. In this repository, there are no rules/, references/, or resources/ folders to lean on, so the core skill file is the main source of truth.

Use the workflow the skill is built for

The setup-deploy guide should follow a simple path: detect the platform, confirm the production endpoint, confirm how deployment health is checked, then persist the result. If the repo has multiple plausible deploy targets, answer those explicitly instead of letting the agent guess. The better the confirmation step, the less likely the resulting CLAUDE.md will encode the wrong platform or status command.

setup-deploy skill FAQ

Is setup-deploy only for full deployment automation?

No. The setup-deploy for Deployment use case is broader than automation alone. It is also for capturing the minimum deployment facts needed so future runs have reliable context.

Do I need to know the hosting platform first?

Not necessarily. One reason people install setup-deploy is to help identify whether the project belongs on Fly.io, Render, Vercel, Netlify, Heroku, GitHub Actions, or a custom path. If you already know the platform, the skill becomes faster and more precise.

Is this better than a normal prompt?

Usually yes, when the goal is to record deployment settings in the repo and make later deploy work repeatable. A normal prompt can explain deployment, but the setup-deploy skill is designed to gather the right inputs and write them into project memory.

What should I check before installing?

Look for whether the project has an existing deploy convention, CI status checks, or environment assumptions that must be preserved. If those are absent, the skill is more likely to save time; if they are already fully standardized, the skill may be redundant.

How to Improve setup-deploy skill

Give the skill concrete deployment evidence

The biggest quality jump comes from supplying exact facts: platform name, production URL, health endpoint, branch name, and any current deploy or status command. If you do not know one item, say what you do know and ask the skill to confirm the rest from the repo.

Resolve ambiguity before writing to CLAUDE.md

The main failure mode is choosing the wrong target from incomplete clues. If the repo could plausibly deploy several ways, tell the skill which signals should win, such as vercel.json, render.yaml, GitHub Actions workflows, or an existing package.json script.

Iterate after the first pass

After the initial setup-deploy run, review the written CLAUDE.md entry for mismatched platform names, stale URLs, or generic status checks. If the configuration feels too broad, narrow it with a second pass that names the exact service, environment, and validation command you want preserved.