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
npx -y skills add jpantsjoha/ai-native-developer-experience --skill release-readinessAssembled 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
-
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.
-
Check all quality gates pass:
make lint— style and static analysis cleanmake typecheck— no type errorsmake test— unit tests greenmake e2e— end-to-end tests green (or equivalent for your stack)- No outstanding HIGH or CRITICAL findings from security scan
-
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?
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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.
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Estimate cost impact — LLM calls, storage writes, egress, third-party API calls. Any unbounded cost vector must be capped or accepted explicitly.
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Confirm monitoring and alerting — what fires when this breaks? Who gets the alert? What is the on-call runbook?
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Check data boundaries — does the release touch PII, regulated data, or cross a tenant boundary? If yes, confirm the appropriate controls are in place.
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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
| Excuse | Counter |
|---|---|
| "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.