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Release readiness

Skill jpantsjoha/ai-native-developer-experience/.agents/skills/release-readiness

Go / no-go gate before any deployment. Checks failure modes, rollback plan, cost, production bar, and definition of done. Trigger before releasing to any environment that carries real consequences.From its SKILL.md

Install
npx -y skills add jpantsjoha/ai-native-developer-experience --skill release-readiness

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 11 stars11 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
  • runs commandsInstructs the agent to run 4 commands, including `make lint` and 3 more.

SKILL.md

3.2 KB, 705 tokens by cl100k_base, as published. Nobody here has run it

Release Readiness

A working demo is not evidence of production readiness. Production readiness is proven through sustained operation, incident handling, cost predictability, and controlled evolution.

This skill enforces the production bar. It produces a go / no-go verdict with a signed checklist. No checklist = no go.

When to use

  • Before deploying to staging or production
  • Before handing a system to another team
  • Before declaring a sprint or milestone complete
  • When someone says "it works on my machine"

Procedure

  1. Validate the definition of done — confirm that acceptance criteria from the spec are met. "Looks good" is not a criterion. Run the actual validation commands.

  2. Check all quality gates pass:

    • make lint — style and static analysis clean
    • make typecheck — no type errors
    • make test — unit tests green
    • make e2e — end-to-end tests green (or equivalent for your stack)
    • No outstanding HIGH or CRITICAL findings from security scan
  3. Name the failure modes — at minimum:

    • What happens if the service is unavailable?
    • What happens under unexpected load?
    • What happens if a dependency (external API, database, queue) is degraded?
    • What is the data-loss risk?
  4. Confirm rollback exists and is tested — a rollback plan that has never been tested is not a rollback plan. If the rollback has not been exercised, flag it.

  5. Estimate cost impact — LLM calls, storage writes, egress, third-party API calls. Any unbounded cost vector must be capped or accepted explicitly.

  6. Confirm monitoring and alerting — what fires when this breaks? Who gets the alert? What is the on-call runbook?

  7. Check data boundaries — does the release touch PII, regulated data, or cross a tenant boundary? If yes, confirm the appropriate controls are in place.

  8. Sign off — record: who reviewed, what was checked, what was accepted as known risk, and the go/no-go verdict.

Outputs

  • Signed release checklist (append to PR or release doc)
  • Go / no-go verdict
  • List of accepted known risks with named owners

Guardrails

  • No go without a rollback plan. "We'll figure it out" is not a rollback.
  • Green CI is necessary, not sufficient. CI validates happy paths. Release readiness validates failure modes.
  • Cost estimates are not optional. An unbounded LLM call in a hot path is a production incident waiting to happen.
  • Monitoring must exist before go-live, not after. "We'll add monitoring later" means the first incident is invisible.

Anti-rationalization table

ExcuseCounter
"CI is green, we're good to go"CI checks known paths. Release readiness checks failure modes CI doesn't cover.
"We'll monitor it after launch"The first failure will be invisible. Add monitoring before go-live.
"Rollback is just redeploy the previous version"Untested. Run the rollback in staging first.
"Cost is fine, it's low traffic"Low traffic + an LLM loop bug = runaway spend. Cap it.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most ship operate skills give in 705 tokens

Counted across 1,077 of the 1,713 authors here whose files we hold, read 2026-09-06

  • Create GitHub releasein 44 of 1077, across 43 files
  • Run the test suitein 30 of 1077, across 25 files
  • Create and push git tagin 27 of 1077, across 26 files
  • Push commits and tagsin 27 of 1077
  • Create annotated tagin 25 of 1077, across 22 files
  • Ensure working tree is cleanin 24 of 1077
  • Check for product marketing context firstin 23 of 1077, across 6 files
  • Commit version bump changesin 22 of 1077, across 21 files
  • Update CHANGELOG.mdin 21 of 1077, across 20 files
  • Structure launch marketing across three channel typesin 20 of 1077, across 5 files
  • Commit and tag the releasein 20 of 1077, across 18 files
  • Update the CHANGELOG for new releasesin 19 of 1077

Said here and by no other author read

  • Validate the definition of done
  • Name the failure modes
  • Check data boundaries
  • Record sign off

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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