deployment-readiness
Skill0 starsChanged 38 days agoMITView on GitHub
Checks whether a web project is ready to ship and closes the gaps, covering the build gate, environment variables, Vercel, serverless and edge runtime fit, database connections and migrations, cron and webhooks, monitoring, a release checklist and a post-deploy smoke test. Use when the user wants to deploy, go live, launch or prepare a release, when a production build or deployment is failing, or when a finished deployment needs verifying.
3 other projects use a version of this.
Adopted by
Most recently taken up by
- frnkgns/Overgeared-Skillstheir own version, first seen Nov 8, 2026
- harness/harness-skillstheir own version, first seen Nov 1, 2026
- georgejieh/agent-skill-library-publictheir own version, first seen Aug 28, 2026
Other versions3 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 3
- harness/harness-skills★ 127same name
- frnkgns/Overgeared-Skills★ 7same name
- georgejieh/agent-skill-library-public★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository7 other files it gives its agents.
- templates/AGENTS.mdAGENTS.md
- backend-engineeringSkill
- database-api-designSkill
- frontend-engineeringSkill
- production-deliverySkill
- security-auditSkill
- testing-qaSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 3 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 3 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 18
Never print, log or copy secret values.
- Very specific: line 19
Do not get a green build by hiding errors: no ignoreBuildErrors, no ignoreDuringBuilds, no blanket @ts-ignore, no skipped tests.
- Distinctive: line 31
Check production fit: Read references/production-pitfalls.md and look for each failure mode in the code.
- Distinctive: line 47
Always include the rollback path.
“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Deployment readiness
The deliverable is a go / no-go verdict the user can trust, with the evidence behind it, plus fixes for whatever blocks a release. "It builds on my machine" and "it works in production" are separated by a known set of differences; most of this skill is about those.
Boundaries
- Prepare the release; do not perform it unless the user explicitly asks in this conversation. Deploying, running migrations against a production database and changing platform environment variables affect live users, so present the exact commands and a rollback path and let the user decide.
- Never print, log or copy secret values. Variable names and "set / missing" are all a report needs. Do not open real env files; the inventory script below works from source code and the example file.
- Do not get a green build by hiding errors: no
ignoreBuildErrors, noignoreDuringBuilds, no blanket@ts-ignore, no skipped tests. If one of these is already in the project, that is a finding.
Approach
- Run the project's own gates in the order it defines them (typically install, typecheck, lint, test, build) and record real output. Fix root causes of failures.
Inventory configuration. From this skill's directory:
node scripts/env-inventory.mjs <project-dir>It reports variables the code reads but the example file does not document, public-prefixed names that look like secrets, env files tracked by git, and whether startup validation exists.
- Check production fit. Read references/production-pitfalls.md and look for each failure mode in the code. These are the things that pass local development and break on the platform: runtime mismatches, connection exhaustion, in-memory state, cron paths, caching defaults, migration commands.
- Work through references/release-checklist.md. Every item gets a status and the evidence for it.
After a deployment exists (preview or production), verify it:
node scripts/smoke.mjs https://<deployment-url> / /login /api/healthGET requests only. It reports status, timing and which security headers are present. Follow it with the critical user flow by hand or with the project's end-to-end tests.
Giving the verdict
State one of Ready, Ready with conditions or Not ready, then the reasons.
Much of production readiness cannot be seen from a repository: whether variables are set on the platform, whether cron actually fires, whether error tracking receives events, whether the database has backups. List these as items for the user to confirm, with where to look. Do not tick them on assumption, and do not call a release verified when the smoke test was not run against the real deployment.
Always include the rollback path. On most platforms rolling back the code is instant and rolling back the database is not, so say which migrations in this release are not backward compatible with the previous code.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

