eigent-ai Ship
Overview
Use this skill to prepare a feature or change for production. The goal is to make launch decisions explicit: what ships, how it rolls out, what is monitored, when to stop, and how to recover.
Workflow
- Identify the release scope, owner, timeline, users affected, dependencies, and risk level.
- Build a pre-launch checklist:
- Tests, migrations, feature flags, documentation, support readiness, analytics, alerts, and runbooks.
- Define rollout strategy:
- Internal, beta, percentage rollout, region/account cohorts, or all-at-once when low risk.
- Specify success metrics and guardrails:
- Product metrics, reliability metrics, error rates, latency, revenue, support volume, and user feedback.
- Create rollback and mitigation steps:
- Flag disablement, revert path, data repair, comms, and owner escalation.
- Plan launch communications for affected teams and users.
- After launch, compare live metrics against expected ranges and decide whether to continue, pause, expand, or roll back.
Output Pattern
- Release summary.
- Pre-launch checklist.
- Rollout stages and entry/exit criteria.
- Monitoring plan.
- Rollback plan.
- Communications plan.
- Post-launch validation steps.
Example Prompts
/ship - We're deploying the new payments flow tomorrow. Walk me through the pre-launch checklist, what to monitor in the first hour, and our rollback plan if error rates spike./ship - Plan a staged rollout for our new recommendation engine. Start at 5% traffic, define success metrics, and set the criteria for each expansion step to 100%./ship - We shipped 3 hours ago. Here are the current metrics [paste]. Is anything outside normal range? Should we roll back or keep going?