Deploy

HARD GATE — Do not deploy without running tests first. Run test or your CI suite before this skill.

HARD GATE — Use this skill from a CI/CD pipeline or post-merge on main/master. Never deploy from a feature branch.

HARD GATE — The deploy skill orchestrates deployment; the smoke-test skill validates post-deploy health. Chain them: deploy → smoke-test.

Orchestrate a full build-to-deployment pipeline: build the artifact, verify it exists and is non-empty, invoke a platform deploy tool (MCP or CLI), poll until the deploy completes or times out, then run a baseline smoke test against the live URL.

Pipeline Stages

build → verify artifact → deploy → wait/retry → smoke

Stage	Description	Failure mode
Build	Execute the project's build command	Non-zero exit: report build error
Verify	Check artifact exists and is non-empty	Missing/empty: report artifact path
Deploy	Invoke platform deploy tool (MCP, Vercel CLI, rsync, etc.)	Non-zero exit: report deploy error
Wait	Poll deploy status every 30s up to DEPLOY_TIMEOUT (default 5 min)	Timeout: report exceeded
Smoke	curl -sSf $DEPLOY_URL as baseline health check	Non-200: report failure

Process

1. Detect build command

Read project manifest files in order to determine the build command:

Manifest	Build command
package.json	npm run build (or scripts.build value)
Cargo.toml	cargo build --release
pyproject.toml / setup.py	Depends on build backend (poetry build, pip install -e ., etc.)
Makefile	make build or first target named build
AGENTS.md / CLAUDE.md	Look for build: in project commands section

If no manifest is found, prompt the user with: "No detected build command. Pass --build 'npm run build' or specify the command."

2. Build the artifact

npm run build

Or the detected command from step 1. If the build fails, exit non-zero and report the build output.

3. Verify the artifact

ARTIFACT_DIR="${ARTIFACT_DIR:-dist}"
if [ ! -d "$ARTIFACT_DIR" ] || [ -z "$(ls -A "$ARTIFACT_DIR" 2>/dev/null)" ]; then
  echo "FAIL: build artifact not found at $ARTIFACT_DIR"
  exit 1
fi

Configurable via $ARTIFACT_DIR environment variable (default: dist/).

4. Deploy to platform

Platform-agnostic — supports multiple deployment targets via environment variables:

Platform	Env var	Example
Vercel	VERCEL_TOKEN, VERCEL_PROJECT_ID	vercel deploy --prod --token $VERCEL_TOKEN
Netlify	NETLIFY_AUTH_TOKEN, NETLIFY_SITE_ID	netlify deploy --prod --auth $NETLIFY_AUTH_TOKEN --dir $ARTIFACT_DIR
Platform MCP	MCP tool call	mcp deploy via your platform MCP server
rsync/SSH	DEPLOY_SSH_USER, DEPLOY_SSH_HOST, DEPLOY_SSH_PATH	rsync -avz $ARTIFACT_DIR/ $DEPLOY_SSH_USER@$DEPLOY_SSH_HOST:$DEPLOY_SSH_PATH
Custom	DEPLOY_COMMAND	Run any deploy command string

The deploy tool is selected by which environment variables are set. If none are configured:

echo "No deploy target configured. Set one of: VERCEL_TOKEN, NETLIFY_AUTH_TOKEN, DEPLOY_SSH_USER+DEPLOY_SSH_HOST, DEPLOY_COMMAND, or MCP deploy tool."
exit 1

5. Wait and poll status

After invoking the deploy command, poll for completion:

See REFERENCE.md

Use exponential backoff for retries on transient failures:

See REFERENCE.md

6. Baseline smoke test

See REFERENCE.md

For comprehensive health-checking, chain to the smoke-test skill:

# After deploy success
bash scripts/run-smoke.sh "$DEPLOY_URL"

7. Three-independent-facts verification (e45s15)

Before declaring deploy success, verify three independent facts — build artifact, platform accept, live/registry reachability. See REFERENCE.md.

Verify

→ verify: command -v curl >/dev/null 2>&1 && test -f skills/smoke-test/SKILL.md