Best use case
Launch Checklist is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
## Trigger
Teams using Launch Checklist 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/launch-checklist/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Launch Checklist Compares
| Feature / Agent | Launch Checklist | 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?
## Trigger
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
# Launch Checklist ## Trigger Activate on "launch checklist", "pre-launch check", "ready to launch?", "launch prep". ## Behavior ### Step 1: Get Context Ask: 1. What are you launching? 2. Launch date 3. How many users affected? 4. Risk level (high/medium/low) ### Step 2: Generate Checklist **Pre-Launch** - [ ] Feature complete and QA'd - [ ] Rollback plan documented and tested - [ ] Success metrics defined with baselines - [ ] Monitoring dashboards set up - [ ] Support team briefed with FAQ - [ ] Release notes drafted - [ ] Feature flag configured (if gradual rollout) **Launch Day** - [ ] Deploy during low-traffic window - [ ] Verify metrics are tracking - [ ] Monitor error rates for 2 hours - [ ] Send internal launch comms - [ ] Publish release notes **Post-Launch (48 hours)** - [ ] Check primary metric vs baseline - [ ] Check guardrail metrics - [ ] Review support tickets for new issues - [ ] Share initial results with team **Post-Launch (1 week)** - [ ] Full metrics review - [ ] Ship or iterate decision - [ ] Retrospective if needed ## Risk Scaling Scale the checklist to risk level: | Risk Level | When | What to Add | |-----------|------|-------------| | **Low** | Config change, copy update, small UI tweak | Minimal — deploy, monitor for 30 min, done | | **Medium** | New feature behind flag, migration with rollback | Full checklist above. 2-hour monitoring window | | **High** | Pricing change, auth flow, data migration, public-facing API | Everything above PLUS: staged rollout (1% → 10% → 50% → 100%), war room channel, exec notification, 24-hour monitoring | ## Example: Good vs Bad Launch Checklist Items **Bad:** "Make sure everything works" **Good:** "Verify signup flow completes end-to-end in staging (email → verification → first dashboard load). Test with Gmail, Outlook, and corporate SSO." **Bad:** "Tell the team" **Good:** "Post in #eng-launches: what shipped, who's on-call, rollback command, link to monitoring dashboard." **Bad:** "Watch metrics" **Good:** "Monitor error rate in Datadog for 2 hours post-deploy. Baseline: 0.3%. Alert threshold: 0.5%. Rollback threshold: 1.0%." ## Rules - Higher risk = more checklist items. Scale accordingly. - Every item needs an owner and a deadline. Not "soon" — a time. - Never launch on Friday afternoons - If rollback takes more than 5 minutes, add more testing time - Every item must be verifiable. "Done" means someone can confirm it, not just feel it.
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