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release-readiness

Validate release readiness with evidence-based go/no-go decisions.

Skill by kindlmann

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About

Validate release readiness with evidence-based go/no-go decisions. Covers go/no-go checklists, smoke test suite design, staged rollout validation, rollback criteria and procedures, and post-deployment verification. Ensures release confidence comes from data, not feelings. Use when: "release ready," "go/no-go," "smoke test," "release checklist," "rollback plan," "staged rollout," "canary deploy." Not for: safe-release techniques (flags, canary, dark launch) applied during the rollout itself — use testing-in-production; scheduled probes that run continuously after release — use synthetic-monitoring; designing new tests from prod telemetry — use observability-driven-testing. Related: testing-in-production, qa-metrics, ci-cd-integration, ai-system-testing.

Use cases: design, testing, devops, data

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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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  • codeload.github.com · found in install command

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  • ~/.claude/skills/release-readiness

What's inside

Skill name
release-readiness
Description
Validate release readiness with evidence-based go/no-go decisions. Covers go/no-go checklists, smoke test suite design, staged rollout validation, rollback criteria and procedures, and post-deployment verification. Ensures release confidence comes from data, not feelings. Use when: "release ready," "go/no-go," "smoke test," "release checklist," "rollback plan," "staged rollout," "canary deploy." Not for: safe-release techniques (flags, canary, dark launch) applied during the rollout itself — use testing-in-production; scheduled probes that run continuously after release — use synthetic-monitoring; designing new tests from prod telemetry — use observability-driven-testing. Related: testing-in-production, qa-metrics, ci-cd-integration, ai-system-testing.
License
MIT
Metadata
author: kindlmann · version: 2.0 · category: process
Instructions
425 lines in SKILL.md · view on GitHub

Before installing

  • Instructions call the network

Files (3)

  • SKILL.md
  • communication-templates.md · references/
  • rollout-automation.md · references/

SKILL.md (first lines)

<objective>
"I think it's fine" ships the bug that the rollback you never practiced can't undo at 6 PM on a Friday. This skill turns "ready to ship" into something measurable: a go/no-go checklist with evidence for each item, a sub-5-minute smoke suite, a staged rollout with metric-gated promotion, rollback thresholds defined before deploy, and post-deployment verification. Every section gives concrete criteria, not aspirations.
</objective>

---

## Discovery Questions

Check `.agents/qa-project-context.md` first — if it exists, use it and skip anything answered there. Then ask only what's missing.

**Release cadence and process:**
- How often do you release, and who makes the go/no-go call? (Continuous/daily/weekly vs engineering lead/QA lead/release manager — sets how heavyweight the checklist should be.)
- Is there a release train schedule or is it ad-hoc?
- How many environments exist between dev and production? (staging, pre-prod, canary)

**Current state:**
- What does the current go/no-go process look like, and is it documented?
- Has a release ever been rolled back? How long did it take? (Reveals whether rollback is real or aspirational.)
- What was the last release incident and its root cause? Any release-blocking bugs right now?

**Infrastructure and capabilities:**
- Do you have rollback capability, and how long does a rollback take?
- Can you do staged/canary deployments?
- Do you have feature flags, and how are they managed? (Decides flag-based vs infra-level rollout.)
- What monitoring and alerting is in place? Are database migrations reversible?

**Team and communication:**
- Who is on-call during and after releases?
- How are stakeholders notified, and is there a release communication channel?
- How are release notes generated?

---

## Core Principles

### 1. Release confidence comes from evidence, not feelings
"I think it's fine" is not a go/no-go criterion. Evidence means: all CI pipelines green, smoke tests pass on staging, performance budgets met, no open P0/P1 bugs. If you can't point to data, you're not ready.

### 2. Smoke tests are the last safety net, not the only safety net
Smoke tests catch catastrophic failures. They are not a substitute for thorough testing throughout the development cycle. If your smoke test suite is the only thing between you and production, you have a process problem upstream.

### 3. Staged rollouts reduce blast radius
Deploying to 100% of users simultaneously means 100% of users are affected by any bug. Staged rollouts (canary, percentage-based, ring-based) let you catch issues when they affect 1% of users instead of all of them.

### 4. Rollback criteria must be defined BEFORE release
If you wait until something is on fire to decide whether to roll back, you'll waste critical minutes debating. Define the criteria in advance, relative to baseline: "If error rate exceeds 2x baseline within 15 minutes, we roll back. No discussion needed." Tie the trigger to your DORA targets — a release whose error rate would push you past your change-failure-rate target, or whose recovery would blow your MTTR target, is one the rollback rule exists to stop.

### 5. Every release is a learning opportunity
Post-deployment verification isn't just about catching bugs. Track what went well, what was slow, what was stressful. Improve the process continuously.

---

## Go/No-Go Checklist

Use this as a template. Adapt it to your context. Every item should be verifiable with evidence, not just "I checked." Store the completed checklist as a versioned artifact (e.g. `RELEASE-<version>.md` or a tracked issue) so sign-off is auditable.

### Automated Checks (Must Pass)

- [ ] **All CI pipelines green** — Unit tests, integration tests, E2E tests, type checking, linting
- [ ] **Smoke test suite passes on staging** — Critical user journeys verified in the staging environment
- [ ] **No open P0/P1 bugs for this release** — Check issue tracker, filter by milestone/label
- [ ] **Performance budgets met** — API response times and bundle size within thresholds; Lighthouse CI for frontend releases (skip Lighthouse for API/backend-only releases — it measures page load, not service health)
- [ ] **Security scan clean** — No high/critical vulnerabilities in `npm audit` / Snyk / Dependabot
- [ ] **API contract tests pass** — No breaking changes to public APIs
- [ ] **Visual regression tests pass** — No unintended visual changes
- [ ] **Accessibility checks pass** — axe-core scan shows no new violations

### Manual Checks (Verify Before Go)

- [ ] **Feature flags reviewed** — Document which flags are enabled/disabled in this release; confirm flag states for production
- [ ] **Monitoring and alerts configured** — New features have corresponding alerts (error rate, latency, business metrics)
- [ ] **Rollback plan documented and tested** — Written procedure exists; rollback has been practiced on staging
- [ ] **Database migrations tested** — Tested forward migration; backward migration verified if schema change is reversible
- [ ] **Third-party dependency changes reviewed** — New or upgraded external dependencies checked for breaking changes
- [ ] **Release notes prepared** — Changelog updated, stakeholder-facing summary written
- [ ] **On-call engineer identified** — Named person is available and has context on the release contents
- [ ] **Communication plan ready** — Stakeholders know the release is happening; support team briefed on changes
- [ ] **No conflicting releases** — Other teams aren't deploying simultaneously
- [ ] **Deploy window confirmed** — Not deploying during peak traffic or before a weekend (unless continuous deployment)

### Risk Assessment

- [ ] **Change scope categorized** — Small (config change, copy update), Medium (new feature, refactor), Large (architecture change, migration)
- [ ] **Blast radius estimated** — What percentage of users could be affected if something goes wrong?
- [ ] **Revert complexity assessed** — Can this be reverted in <5 minutes? Does reverting require a data migration?

---

## Smoke Test Suite Design

### What to Include

Smoke tests cover **critical user journeys only**. If these fail, the application is fundamentally broken.

**Typical smoke test suite (5-8 tests):**

1. **Application health** — Homepage loads, returns 200, no JavaScript errors in console
2. **Authentication** — User can log in with valid credentials, session is established
3. **Core workflow** — The primary value-delivering action works (e.g., create a document, submit a form, add to cart or complete a purchase flow)
4. **Data retrieval** — Key data loads correctly (dashboard populates, search returns results, product page loads)
5. **Payment/transaction** (if applicable) — Payment flow completes with test credentials
6. **API health** — Primary API endpoints return valid responses with correct schemas
7. **Navigation** — Critical navigation paths work (deep links, redirects, menu items)
8. **Error handling** — Application shows a user-friendly error page for invalid routes (404)

### What NOT to Include

- Edge cases (those belong in regression tests)
- Visual perfection (that belongs in visual regression tests)
- Performance benchmarks (that belongs in performance tests)
- Exhaustive form validation (that belongs in unit/integration tests)

### Keeping It Fast

Target: **under 5 minutes** for the entire smoke suite.

- Run tests in parallel where possible
- Use API calls instead of UI interactions for setup (create test user via API, not through registration form)
- Skip non-critical assertions (don't check exact copy text, check that elements exist)

From ExelAlfanso/puppets, MIT.

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Last commit (this folder)
Oct 1, 2026 (27 days ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
2.0
License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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release-readiness skill. Agent Mart. https://agentmart.dev/skills/exelalfanso-release-readiness (last updated 2026-10-24)