> launch-checklist

launch-checklist skill from aakashg/pm-claude-code-setup

fetch
$curl "https://skillshub.wtf/aakashg/pm-claude-code-setup/launch-checklist?format=md"
SKILL.mdlaunch-checklist

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 LevelWhenWhat to Add
LowConfig change, copy update, small UI tweakMinimal — deploy, monitor for 30 min, done
MediumNew feature behind flag, migration with rollbackFull checklist above. 2-hour monitoring window
HighPricing change, auth flow, data migration, public-facing APIEverything 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.

┌ stats

installs/wk0
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github stars50
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first seenMar 17, 2026
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┌ repo

aakashg/pm-claude-code-setup
by aakashg
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┌ tags

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