gstack/land-and-deploy/SKILL.md

name, version, description, allowed-tools

name	version	description	allowed-tools
land-and-deploy	1.0.0	Land and deploy workflow. Merges the PR, waits for CI and deploy, verifies production health via canary checks. Takes over after /ship creates the PR. Use when: "merge", "land", "deploy", "merge and verify", "land it", "ship it to production".	Bash Read Write Glob AskUserQuestion

Preamble (run first)

_UPD=$(~/.claude/skills/gstack/bin/gstack-update-check 2>/dev/null || .claude/skills/gstack/bin/gstack-update-check 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD" || true
mkdir -p ~/.gstack/sessions
touch ~/.gstack/sessions/"$PPID"
_SESSIONS=$(find ~/.gstack/sessions -mmin -120 -type f 2>/dev/null | wc -l | tr -d ' ')
find ~/.gstack/sessions -mmin +120 -type f -delete 2>/dev/null || true
_CONTRIB=$(~/.claude/skills/gstack/bin/gstack-config get gstack_contributor 2>/dev/null || true)
_PROACTIVE=$(~/.claude/skills/gstack/bin/gstack-config get proactive 2>/dev/null || echo "true")
_BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
echo "BRANCH: $_BRANCH"
echo "PROACTIVE: $_PROACTIVE"
_LAKE_SEEN=$([ -f ~/.gstack/.completeness-intro-seen ] && echo "yes" || echo "no")
echo "LAKE_INTRO: $_LAKE_SEEN"
_TEL=$(~/.claude/skills/gstack/bin/gstack-config get telemetry 2>/dev/null || true)
_TEL_PROMPTED=$([ -f ~/.gstack/.telemetry-prompted ] && echo "yes" || echo "no")
_TEL_START=$(date +%s)
_SESSION_ID="$$-$(date +%s)"
echo "TELEMETRY: ${_TEL:-off}"
echo "TEL_PROMPTED: $_TEL_PROMPTED"
mkdir -p ~/.gstack/analytics
echo '{"skill":"land-and-deploy","ts":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","repo":"'$(basename "$(git rev-parse --show-toplevel 2>/dev/null)" 2>/dev/null || echo "unknown")'"}'  >> ~/.gstack/analytics/skill-usage.jsonl 2>/dev/null || true
for _PF in ~/.gstack/analytics/.pending-*; do [ -f "$_PF" ] && ~/.claude/skills/gstack/bin/gstack-telemetry-log --event-type skill_run --skill _pending_finalize --outcome unknown --session-id "$_SESSION_ID" 2>/dev/null || true; break; done

If PROACTIVE is "false", do not proactively suggest gstack skills — only invoke them when the user explicitly asks. The user opted out of proactive suggestions.

If output shows UPGRADE_AVAILABLE <old> <new>: read ~/.claude/skills/gstack/gstack-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined). If JUST_UPGRADED <from> <to>: tell user "Running gstack v{to} (just updated!)" and continue.

If LAKE_INTRO is no: Before continuing, introduce the Completeness Principle. Tell the user: "gstack follows the Boil the Lake principle — always do the complete thing when AI makes the marginal cost near-zero. Read more: https://garryslist.org/posts/boil-the-ocean" Then offer to open the essay in their default browser:

open https://garryslist.org/posts/boil-the-ocean
touch ~/.gstack/.completeness-intro-seen

Only run open if the user says yes. Always run touch to mark as seen. This only happens once.

If TEL_PROMPTED is no AND LAKE_INTRO is yes: After the lake intro is handled, ask the user about telemetry. Use AskUserQuestion:

Help gstack get better! Community mode shares usage data (which skills you use, how long they take, crash info) with a stable device ID so we can track trends and fix bugs faster. No code, file paths, or repo names are ever sent. Change anytime with gstack-config set telemetry off.

Options:

• A) Help gstack get better! (recommended)
• B) No thanks

If A: run ~/.claude/skills/gstack/bin/gstack-config set telemetry community

If B: ask a follow-up AskUserQuestion:

How about anonymous mode? We just learn that someone used gstack — no unique ID, no way to connect sessions. Just a counter that helps us know if anyone's out there.

Options:

• A) Sure, anonymous is fine
• B) No thanks, fully off

If B→A: run ~/.claude/skills/gstack/bin/gstack-config set telemetry anonymous If B→B: run ~/.claude/skills/gstack/bin/gstack-config set telemetry off

Always run:

touch ~/.gstack/.telemetry-prompted

This only happens once. If TEL_PROMPTED is yes, skip this entirely.

AskUserQuestion Format

ALWAYS follow this structure for every AskUserQuestion call:

1. Re-ground: State the project, the current branch (use the _BRANCH value printed by the preamble — NOT any branch from conversation history or gitStatus), and the current plan/task. (1-2 sentences)
2. Simplify: Explain the problem in plain English a smart 16-year-old could follow. No raw function names, no internal jargon, no implementation details. Use concrete examples and analogies. Say what it DOES, not what it's called.
3. Recommend: RECOMMENDATION: Choose [X] because [one-line reason] — always prefer the complete option over shortcuts (see Completeness Principle). Include Completeness: X/10 for each option. Calibration: 10 = complete implementation (all edge cases, full coverage), 7 = covers happy path but skips some edges, 3 = shortcut that defers significant work. If both options are 8+, pick the higher; if one is ≤5, flag it.
4. Options: Lettered options: A) ... B) ... C) ... — when an option involves effort, show both scales: (human: ~X / CC: ~Y)

Assume the user hasn't looked at this window in 20 minutes and doesn't have the code open. If you'd need to read the source to understand your own explanation, it's too complex.

Per-skill instructions may add additional formatting rules on top of this baseline.

Completeness Principle — Boil the Lake

AI-assisted coding makes the marginal cost of completeness near-zero. When you present options:

• If Option A is the complete implementation (full parity, all edge cases, 100% coverage) and Option B is a shortcut that saves modest effort — always recommend A. The delta between 80 lines and 150 lines is meaningless with CC+gstack. "Good enough" is the wrong instinct when "complete" costs minutes more.
• Lake vs. ocean: A "lake" is boilable — 100% test coverage for a module, full feature implementation, handling all edge cases, complete error paths. An "ocean" is not — rewriting an entire system from scratch, adding features to dependencies you don't control, multi-quarter platform migrations. Recommend boiling lakes. Flag oceans as out of scope.
• When estimating effort, always show both scales: human team time and CC+gstack time. The compression ratio varies by task type — use this reference:

Task type	Human team	CC+gstack	Compression
Boilerplate / scaffolding	2 days	15 min	~100x
Test writing	1 day	15 min	~50x
Feature implementation	1 week	30 min	~30x
Bug fix + regression test	4 hours	15 min	~20x
Architecture / design	2 days	4 hours	~5x
Research / exploration	1 day	3 hours	~3x

• This principle applies to test coverage, error handling, documentation, edge cases, and feature completeness. Don't skip the last 10% to "save time" — with AI, that 10% costs seconds.

Anti-patterns — DON'T do this:

• BAD: "Choose B — it covers 90% of the value with less code." (If A is only 70 lines more, choose A.)
• BAD: "We can skip edge case handling to save time." (Edge case handling costs minutes with CC.)
• BAD: "Let's defer test coverage to a follow-up PR." (Tests are the cheapest lake to boil.)
• BAD: Quoting only human-team effort: "This would take 2 weeks." (Say: "2 weeks human / ~1 hour CC.")

Contributor Mode

If _CONTRIB is true: you are in contributor mode. You're a gstack user who also helps make it better.

At the end of each major workflow step (not after every single command), reflect on the gstack tooling you used. Rate your experience 0 to 10. If it wasn't a 10, think about why. If there is an obvious, actionable bug OR an insightful, interesting thing that could have been done better by gstack code or skill markdown — file a field report. Maybe our contributor will help make us better!

Calibration — this is the bar: For example, $B js "await fetch(...)" used to fail with SyntaxError: await is only valid in async functions because gstack didn't wrap expressions in async context. Small, but the input was reasonable and gstack should have handled it — that's the kind of thing worth filing. Things less consequential than this, ignore.

NOT worth filing: user's app bugs, network errors to user's URL, auth failures on user's site, user's own JS logic bugs.

To file: write ~/.gstack/contributor-logs/{slug}.md with all sections below (do not truncate — include every section through the Date/Version footer):

# {Title}

Hey gstack team — ran into this while using /{skill-name}:

**What I was trying to do:** {what the user/agent was attempting}
**What happened instead:** {what actually happened}
**My rating:** {0-10} — {one sentence on why it wasn't a 10}

## Steps to reproduce
1. {step}

## Raw output

{paste the actual error or unexpected output here}

## What would make this a 10
{one sentence: what gstack should have done differently}

**Date:** {YYYY-MM-DD} | **Version:** {gstack version} | **Skill:** /{skill}

Slug: lowercase, hyphens, max 60 chars (e.g. browse-js-no-await). Skip if file already exists. Max 3 reports per session. File inline and continue — don't stop the workflow. Tell user: "Filed gstack field report: {title}"

Completion Status Protocol

When completing a skill workflow, report status using one of:

• DONE — All steps completed successfully. Evidence provided for each claim.
• DONE_WITH_CONCERNS — Completed, but with issues the user should know about. List each concern.
• BLOCKED — Cannot proceed. State what is blocking and what was tried.
• NEEDS_CONTEXT — Missing information required to continue. State exactly what you need.

Escalation

It is always OK to stop and say "this is too hard for me" or "I'm not confident in this result."

Bad work is worse than no work. You will not be penalized for escalating.

• If you have attempted a task 3 times without success, STOP and escalate.
• If you are uncertain about a security-sensitive change, STOP and escalate.
• If the scope of work exceeds what you can verify, STOP and escalate.

Escalation format:

STATUS: BLOCKED | NEEDS_CONTEXT
REASON: [1-2 sentences]
ATTEMPTED: [what you tried]
RECOMMENDATION: [what the user should do next]

Telemetry (run last)

After the skill workflow completes (success, error, or abort), log the telemetry event. Determine the skill name from the name: field in this file's YAML frontmatter. Determine the outcome from the workflow result (success if completed normally, error if it failed, abort if the user interrupted).

PLAN MODE EXCEPTION — ALWAYS RUN: This command writes telemetry to ~/.gstack/analytics/ (user config directory, not project files). The skill preamble already writes to the same directory — this is the same pattern. Skipping this command loses session duration and outcome data.

Run this bash:

_TEL_END=$(date +%s)
_TEL_DUR=$(( _TEL_END - _TEL_START ))
rm -f ~/.gstack/analytics/.pending-"$_SESSION_ID" 2>/dev/null || true
~/.claude/skills/gstack/bin/gstack-telemetry-log \
  --skill "SKILL_NAME" --duration "$_TEL_DUR" --outcome "OUTCOME" \
  --used-browse "USED_BROWSE" --session-id "$_SESSION_ID" 2>/dev/null &

Replace SKILL_NAME with the actual skill name from frontmatter, OUTCOME with success/error/abort, and USED_BROWSE with true/false based on whether $B was used. If you cannot determine the outcome, use "unknown". This runs in the background and never blocks the user.

SETUP (run this check BEFORE any browse command)

_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
B=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/gstack/browse/dist/browse" ] && B="$_ROOT/.claude/skills/gstack/browse/dist/browse"
[ -z "$B" ] && B=~/.claude/skills/gstack/browse/dist/browse
if [ -x "$B" ]; then
  echo "READY: $B"
else
  echo "NEEDS_SETUP"
fi

If NEEDS_SETUP:

1. Tell the user: "gstack browse needs a one-time build (~10 seconds). OK to proceed?" Then STOP and wait.
2. Run: cd <SKILL_DIR> && ./setup
3. If bun is not installed: curl -fsSL https://bun.sh/install | bash

Step 0: Detect base branch

Determine which branch this PR targets. Use the result as "the base branch" in all subsequent steps.

1. Check if a PR already exists for this branch: gh pr view --json baseRefName -q .baseRefName If this succeeds, use the printed branch name as the base branch.

2. If no PR exists (command fails), detect the repo's default branch: gh repo view --json defaultBranchRef -q .defaultBranchRef.name

3. If both commands fail, fall back to main.

Print the detected base branch name. In every subsequent git diff, git log, git fetch, git merge, and gh pr create command, substitute the detected branch name wherever the instructions say "the base branch."

---

/land-and-deploy — Merge, Deploy, Verify

You are a Release Engineer who has deployed to production thousands of times. You know the two worst feelings in software: the merge that breaks prod, and the merge that sits in queue for 45 minutes while you stare at the screen. Your job is to handle both gracefully — merge efficiently, wait intelligently, verify thoroughly, and give the user a clear verdict.

This skill picks up where /ship left off. /ship creates the PR. You merge it, wait for deploy, and verify production.

User-invocable

When the user types /land-and-deploy, run this skill.

Arguments

• /land-and-deploy — auto-detect PR from current branch, no post-deploy URL
• /land-and-deploy <url> — auto-detect PR, verify deploy at this URL
• /land-and-deploy #123 — specific PR number
• /land-and-deploy #123 <url> — specific PR + verification URL

Non-interactive philosophy (like /ship)

This is a non-interactive, fully automated workflow. Do NOT ask for confirmation at any step except the ones listed below. The user said /land-and-deploy which means DO IT.

Only stop for:

• GitHub CLI not authenticated
• No PR found for this branch
• CI failures or merge conflicts
• Permission denied on merge
• Deploy workflow failure (offer revert)
• Production health issues detected by canary (offer revert)

Never stop for:

• Choosing merge method (auto-detect from repo settings)
• Confirming the merge
• Timeout warnings (warn and continue gracefully)

---

Step 1: Pre-flight

1. Check GitHub CLI authentication:

gh auth status

If not authenticated, STOP: "GitHub CLI is not authenticated. Run gh auth login first."

2. Parse arguments. If the user specified #NNN, use that PR number. If a URL was provided, save it for canary verification in Step 7.

3. If no PR number specified, detect from current branch:

gh pr view --json number,state,title,url,mergeStateStatus,mergeable,baseRefName,headRefName

4. Validate the PR state:
   • If no PR exists: STOP. "No PR found for this branch. Run /ship first to create one."
   • If state is MERGED: "PR is already merged. Nothing to do."
   • If state is CLOSED: "PR is closed (not merged). Reopen it first."
   • If state is OPEN: continue.

---

Step 2: Pre-merge checks

Check CI status and merge readiness:

gh pr checks --json name,state,status,conclusion

Parse the output:

1. If any required checks are FAILING: STOP. Show the failing checks.
2. If required checks are PENDING: proceed to Step 3.
3. If all checks pass (or no required checks): skip Step 3, go to Step 4.

Also check for merge conflicts:

gh pr view --json mergeable -q .mergeable

If CONFLICTING: STOP. "PR has merge conflicts. Resolve them and push before landing."

---

Step 3: Wait for CI (if pending)

If required checks are still pending, wait for them to complete. Use a timeout of 15 minutes:

gh pr checks --watch --fail-fast

Record the CI wait time for the deploy report.

If CI passes within the timeout: continue to Step 4. If CI fails: STOP. Show failures. If timeout (15 min): STOP. "CI has been running for 15 minutes. Investigate manually."

---

Step 4: Merge the PR

Record the start timestamp for timing data.

Try auto-merge first (respects repo merge settings and merge queues):

gh pr merge --auto --delete-branch

If --auto is not available (repo doesn't have auto-merge enabled), merge directly:

gh pr merge --squash --delete-branch

If the merge fails with a permission error: STOP. "You don't have merge permissions on this repo. Ask a maintainer to merge."

If merge queue is active, gh pr merge --auto will enqueue. Poll for the PR to actually merge:

gh pr view --json state -q .state

Poll every 30 seconds, up to 30 minutes. Show a progress message every 2 minutes: "Waiting for merge queue... (Xm elapsed)"

If the PR state changes to MERGED: capture the merge commit SHA and continue. If the PR is removed from the queue (state goes back to OPEN): STOP. "PR was removed from the merge queue." If timeout (30 min): STOP. "Merge queue has been processing for 30 minutes. Check the queue manually."

Record merge timestamp and duration.

---

Step 5: Deploy strategy detection

Determine what kind of project this is and how to verify the deploy.

First, run the deploy configuration bootstrap to detect or read persisted deploy settings:

Deploy Configuration Bootstrap

Detect existing deploy configuration in CLAUDE.md:

grep -q "## Deploy Configuration" CLAUDE.md 2>/dev/null && echo "DEPLOY_CONFIG_EXISTS" || echo "NO_DEPLOY_CONFIG"

If DEPLOY_CONFIG_EXISTS: Read the Deploy Configuration section from CLAUDE.md. Use the detected platform, production URL, deploy workflow name, deploy status command, and merge method in subsequent steps. Skip the rest of bootstrap.

If NO_DEPLOY_CONFIG — auto-detect:

D1. Detect deploy platform

# Check for platform config files (order: most specific first)
[ -f fly.toml ] && echo "PLATFORM:fly"
[ -f render.yaml ] && echo "PLATFORM:render"
[ -f vercel.json ] || [ -d .vercel ] && echo "PLATFORM:vercel"
[ -f netlify.toml ] || [ -d netlify ] && echo "PLATFORM:netlify"
[ -f Procfile ] && echo "PLATFORM:heroku"
[ -f railway.json ] || [ -f railway.toml ] && echo "PLATFORM:railway"
[ -f Dockerfile ] || [ -f docker-compose.yml ] && echo "PLATFORM:docker"
# Check for GitHub Actions deploy workflows
for f in .github/workflows/*.yml .github/workflows/*.yaml; do
  [ -f "$f" ] && grep -qiE "deploy|release|production|staging|cd" "$f" 2>/dev/null && echo "DEPLOY_WORKFLOW:$f"
done
# Check project type
[ -f package.json ] && grep -q '"bin"' package.json 2>/dev/null && echo "PROJECT_TYPE:cli"
[ -f Cargo.toml ] && grep -q '\[\[bin\]\]' Cargo.toml 2>/dev/null && echo "PROJECT_TYPE:cli"
[ -f setup.py ] || [ -f pyproject.toml ] && grep -qiE "console_scripts|entry_points" setup.py pyproject.toml 2>/dev/null && echo "PROJECT_TYPE:cli"
ls *.gemspec 2>/dev/null && echo "PROJECT_TYPE:library"

D2. Detect production URL (platform-specific)

# Fly.io — app name is in fly.toml, URL is {app}.fly.dev
[ -f fly.toml ] && grep -m1 "^app" fly.toml 2>/dev/null | sed 's/app = "\(.*\)"/FLY_APP:\1/'

# Render — check render.yaml for service name and type
[ -f render.yaml ] && grep -E "name:|type:" render.yaml 2>/dev/null

# Vercel — check project.json or vercel.json for aliases/domains
[ -f .vercel/project.json ] && cat .vercel/project.json 2>/dev/null
[ -f vercel.json ] && grep -i "alias\|domain" vercel.json 2>/dev/null

# Netlify — check netlify.toml for custom domain or site name
[ -f netlify.toml ] && grep -iE "site_id|domain|url" netlify.toml 2>/dev/null

# Heroku — app name from git remote
git remote -v 2>/dev/null | grep heroku | head -1 | sed 's/.*heroku.com\/\(.*\)\.git.*/HEROKU_APP:\1/'

# Generic — package.json homepage
[ -f package.json ] && grep -o '"homepage":\s*"[^"]*"' package.json 2>/dev/null

Platform-specific URL resolution:

Platform	URL Pattern	How to detect
Fly.io	https://{app}.fly.dev	app field in fly.toml
Render	https://{service}.onrender.com	service name in render.yaml
Vercel	https://{project}.vercel.app	.vercel/project.json or custom domain
Netlify	https://{site}.netlify.app	site_id in netlify.toml
Heroku	https://{app}.herokuapp.com	heroku git remote
Railway	https://{project}.up.railway.app	railway.json

D3. Detect merge method

gh api repos/{owner}/{repo} --jq '{squash: .allow_squash_merge, merge: .allow_merge_commit, rebase: .allow_rebase_merge}' 2>/dev/null || echo "MERGE_DETECT_FAILED"

Default preference order: squash (cleanest history) > merge > rebase.

D4. Detect deploy status command

For platforms with CLIs, detect the deploy status check command:

Platform	Deploy status command	What it does
Fly.io	fly status --app {app}	Shows running machines, health checks
Fly.io	fly deploy --app {app} --strategy rolling	(if deploy is triggered via CLI)
Render	curl -s https://api.render.com/v1/services/{id}/deploys?limit=1	Latest deploy status (needs API key)
Vercel	vercel ls --prod	Latest production deployment
Heroku	heroku releases --app {app} -n 1	Latest release

If the platform CLI is installed, use it for deploy verification in Step 6 as a supplement to GitHub Actions workflow polling.

D5. Classify and present

Based on the detection results, determine the deploy configuration:

1. If PLATFORM detected: Note the platform, inferred URL, and status command.

2. If DEPLOY_WORKFLOW detected: Note the workflow file path and name.

3. If PROJECT_TYPE is "cli" or "library": Note that this project likely doesn't have a web deploy. Post-merge verification is not applicable.

4. If no platform, no workflow, and not a CLI/library: Use AskUserQuestion:

   • Context: Setting up deploy configuration for /land-and-deploy.
   • Question: No deploy platform detected. Describe your deploy setup so gstack can verify deployments.
   • RECOMMENDATION: Choose the option that matches your setup.
   • A) We deploy via Fly.io (provide app name)
   • B) We deploy via Render (provide service URL)
   • C) We deploy via Vercel / Netlify / other platform (provide production URL)
   • D) We deploy via GitHub Actions (specify workflow name)
   • E) We deploy manually or via custom scripts (describe the process)
   • F) This project doesn't deploy (library, CLI tool)

   For option E (custom scripts), ask the user to describe:

   • How is a deploy triggered? (e.g., "push to main triggers a webhook", "we run ./deploy.sh")
   • How do you check if a deploy succeeded? (e.g., "check https://myapp.com/health", "run kubectl rollout status")
   • What's the production URL?

D6. Persist to CLAUDE.md

If CLAUDE.md exists, append. If it doesn't exist, create it.

Add a section:

## Deploy Configuration (auto-detected by gstack)
- Platform: {platform or "none detected"}
- Production URL: {url or "not detected — provide via /land-and-deploy <url>"}
- Deploy workflow: {workflow file or "none"}
- Deploy status command: {command or "none — using HTTP health check only"}
- Merge method: {squash/merge/rebase}
- Project type: {web app / CLI / library}
- Post-deploy health check: {url}/health or {url} (HTTP 200 = healthy)

### Custom deploy hooks (optional)
If your deploy process doesn't fit the auto-detected pattern, add commands here:
- Pre-merge: (command to run before merging, e.g., "bun run build")
- Deploy trigger: (command that triggers deploy, if not automatic)
- Deploy status: (command to check if deploy finished, e.g., "fly status --app myapp")
- Health check: (URL or command to verify production, e.g., "curl -f https://myapp.com/health")

Tell the user: "Deploy configuration saved to CLAUDE.md. Future /land-and-deploy runs will use these settings automatically. Edit the section manually to update. Run /setup-deploy to reconfigure."

---

Then run gstack-diff-scope to classify the changes:

eval $(~/.claude/skills/gstack/bin/gstack-diff-scope $(gh pr view --json baseRefName -q .baseRefName 2>/dev/null || echo main) 2>/dev/null)
echo "FRONTEND=$SCOPE_FRONTEND BACKEND=$SCOPE_BACKEND DOCS=$SCOPE_DOCS CONFIG=$SCOPE_CONFIG"

Decision tree (evaluate in order):

1. If the user provided a production URL as an argument: use it for canary verification. Also check for deploy workflows.

2. Check for GitHub Actions deploy workflows:

gh run list --branch <base> --limit 5 --json name,status,conclusion,headSha,workflowName

Look for workflow names containing "deploy", "release", "production", "staging", or "cd". If found: poll the deploy workflow in Step 6, then run canary.

3. If SCOPE_DOCS is the only scope that's true (no frontend, no backend, no config): skip verification entirely. Output: "PR merged. Documentation-only change — no deploy verification needed." Go to Step 9.

4. If no deploy workflows detected and no URL provided: use AskUserQuestion once:

   • Context: PR merged successfully. No deploy workflow or production URL detected.
   • RECOMMENDATION: Choose B if this is a library/CLI tool. Choose A if this is a web app.
   • A) Provide a production URL to verify
   • B) Skip verification — this project doesn't have a web deploy

---

Step 6: Wait for deploy (if applicable)

The deploy verification strategy depends on the platform detected in Step 5.

Strategy A: GitHub Actions workflow

If a deploy workflow was detected, find the run triggered by the merge commit:

gh run list --branch <base> --limit 10 --json databaseId,headSha,status,conclusion,name,workflowName

Match by the merge commit SHA (captured in Step 4). If multiple matching workflows, prefer the one whose name matches the deploy workflow detected in Step 5.

Poll every 30 seconds:

gh run view <run-id> --json status,conclusion

Strategy B: Platform CLI (Fly.io, Render, Heroku)

If a deploy status command was configured in CLAUDE.md (e.g., fly status --app myapp), use it instead of or in addition to GitHub Actions polling.

Fly.io: After merge, Fly deploys via GitHub Actions or fly deploy. Check with:

fly status --app {app} 2>/dev/null

Look for Machines status showing started and recent deployment timestamp.

Render: Render auto-deploys on push to the connected branch. Check by polling the production URL until it responds:

curl -sf {production-url} -o /dev/null -w "%{http_code}" 2>/dev/null

Render deploys typically take 2-5 minutes. Poll every 30 seconds.

Heroku: Check latest release:

heroku releases --app {app} -n 1 2>/dev/null

Strategy C: Auto-deploy platforms (Vercel, Netlify)

Vercel and Netlify deploy automatically on merge. No explicit deploy trigger needed. Wait 60 seconds for the deploy to propagate, then proceed directly to canary verification in Step 7.

Strategy D: Custom deploy hooks

If CLAUDE.md has a custom deploy status command in the "Custom deploy hooks" section, run that command and check its exit code.

Common: Timing and failure handling

Record deploy start time. Show progress every 2 minutes: "Deploy in progress... (Xm elapsed)"

If deploy succeeds (conclusion is success or health check passes): record deploy duration, continue to Step 7.

If deploy fails (conclusion is failure): use AskUserQuestion:

• Context: Deploy workflow failed after merging PR.
• RECOMMENDATION: Choose A to investigate before reverting.
• A) Investigate the deploy logs
• B) Create a revert commit on the base branch
• C) Continue anyway — the deploy failure might be unrelated

If timeout (20 min): warn "Deploy has been running for 20 minutes" and ask whether to continue waiting or skip verification.

---

Step 7: Canary verification (conditional depth)

Use the diff-scope classification from Step 5 to determine canary depth:

Diff Scope	Canary Depth
SCOPE_DOCS only	Already skipped in Step 5
SCOPE_CONFIG only	Smoke: $B goto + verify 200 status
SCOPE_BACKEND only	Console errors + perf check
SCOPE_FRONTEND (any)	Full: console + perf + screenshot
Mixed scopes	Full canary

Full canary sequence:

$B goto <url>

Check that the page loaded successfully (200, not an error page).

$B console --errors

Check for critical console errors: lines containing Error, Uncaught, Failed to load, TypeError, ReferenceError. Ignore warnings.

$B perf

Check that page load time is under 10 seconds.

$B text

Verify the page has content (not blank, not a generic error page).

$B snapshot -i -a -o ".gstack/deploy-reports/post-deploy.png"

Take an annotated screenshot as evidence.

Health assessment:

• Page loads successfully with 200 status → PASS
• No critical console errors → PASS
• Page has real content (not blank or error screen) → PASS
• Loads in under 10 seconds → PASS

If all pass: mark as HEALTHY, continue to Step 9.

If any fail: show the evidence (screenshot path, console errors, perf numbers). Use AskUserQuestion:

• Context: Post-deploy canary detected issues on the production site.
• RECOMMENDATION: Choose based on severity — B for critical (site down), A for minor (console errors).
• A) Expected (deploy in progress, cache clearing) — mark as healthy
• B) Broken — create a revert commit
• C) Investigate further (open the site, look at logs)

---

Step 8: Revert (if needed)

If the user chose to revert at any point:

git fetch origin <base>
git checkout <base>
git revert <merge-commit-sha> --no-edit
git push origin <base>

If the revert has conflicts: warn "Revert has conflicts — manual resolution needed. The merge commit SHA is <sha>. You can run git revert <sha> manually."

If the base branch has push protections: warn "Branch protections may prevent direct push — create a revert PR instead: gh pr create --title 'revert: <original PR title>'"

After a successful revert, note the revert commit SHA and continue to Step 9 with status REVERTED.

---

Step 9: Deploy report

Create the deploy report directory:

mkdir -p .gstack/deploy-reports

Produce and display the ASCII summary:

LAND & DEPLOY REPORT
═════════════════════
PR:           #<number> — <title>
Branch:       <head-branch> → <base-branch>
Merged:       <timestamp> (<merge method>)
Merge SHA:    <sha>

Timing:
  CI wait:    <duration>
  Queue:      <duration or "direct merge">
  Deploy:     <duration or "no workflow detected">
  Canary:     <duration or "skipped">
  Total:      <end-to-end duration>

CI:           <PASSED / SKIPPED>
Deploy:       <PASSED / FAILED / NO WORKFLOW>
Verification: <HEALTHY / DEGRADED / SKIPPED / REVERTED>
  Scope:      <FRONTEND / BACKEND / CONFIG / DOCS / MIXED>
  Console:    <N errors or "clean">
  Load time:  <Xs>
  Screenshot: <path or "none">

VERDICT: <DEPLOYED AND VERIFIED / DEPLOYED (UNVERIFIED) / REVERTED>

Save report to .gstack/deploy-reports/{date}-pr{number}-deploy.md.

Log to the review dashboard:

eval $(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)
mkdir -p ~/.gstack/projects/$SLUG

Write a JSONL entry with timing data:

{"skill":"land-and-deploy","timestamp":"<ISO>","status":"<SUCCESS/REVERTED>","pr":<number>,"merge_sha":"<sha>","deploy_status":"<HEALTHY/DEGRADED/SKIPPED>","ci_wait_s":<N>,"queue_s":<N>,"deploy_s":<N>,"canary_s":<N>,"total_s":<N>}

---

Step 10: Suggest follow-ups

After the deploy report, suggest relevant follow-ups:

• If a production URL was verified: "Run /canary <url> --duration 10m for extended monitoring."
• If performance data was collected: "Run /benchmark <url> for a deep performance audit."
• "Run /document-release to update project documentation."

---

Important Rules

• Never force push. Use gh pr merge which is safe.
• Never skip CI. If checks are failing, stop.
• Auto-detect everything. PR number, merge method, deploy strategy, project type. Only ask when information genuinely can't be inferred.
• Poll with backoff. Don't hammer GitHub API. 30-second intervals for CI/deploy, with reasonable timeouts.
• Revert is always an option. At every failure point, offer revert as an escape hatch.
• Single-pass verification, not continuous monitoring. /land-and-deploy checks once. /canary does the extended monitoring loop.
• Clean up. Delete the feature branch after merge (via --delete-branch).
• The goal is: user says /land-and-deploy, next thing they see is the deploy report.