Resource
Markdown Output Prompt — Lock the Document Structure
The contract that stops AI documents from restructuring themselves: a pinned section skeleton, forced tables, and strict consistency rules.
Post-Deploy Smoke Test Prompt
Confirm a deploy is actually healthy — a short, ordered smoke-test checklist of the critical paths to verify in the first minutes after shipping.
Overview
A green deploy pipeline means the code deployed, not that the product works. This prompt builds a post-deploy smoke test: the handful of critical user and system paths to verify in the first minutes after release, what a pass looks like for each, and the threshold of failures that triggers a rollback. It's the difference between 'deployed' and 'confirmed working.'
How to use this resource
-
Describe what just shipped
Note the change, the environment, and the critical user and system paths it could affect. The smoke test verifies these in the first minutes after release.
-
Open this resource in Markdown Output Builder
Load the prompt into Markdown Output Builder and fill in the deploy. It returns the smoke-test checklist as a clean, ordered Markdown list you can run straight away.
-
Walk through the critical paths
Read the handful of paths to verify, what a pass looks like for each, and the failure threshold that triggers a rollback.
-
Run it and act on the result
Work the checklist right after deploy, and if failures cross the threshold, roll back rather than leave a green pipeline mistaken for a working product.
Why This Works
- Green pipeline ≠ working product; the smoke test closes that gap
- A pre-agreed rollback threshold removes hesitation under pressure
- Prioritizing by impact means the worst problems surface first
Best for
- Any production deploy of a user-facing system
- Releases where a broken core path is high-impact
- Teams that currently 'deploy and hope'
Not for
- A full regression suite — this is the fast critical-path check
- Pre-deploy readiness — use the Release Readiness Checklist
Use cases
- Verifying the critical paths right after a deploy
- Catching a broken release before users report it
- Giving on-call a fast 'is it healthy?' checklist
FAQ
Does the post-deploy smoke test prompt actually roll back my release if checks fail?
It does not act on your infrastructure. The ROLLBACK THRESHOLD section defines how many or which failures mean roll back now versus investigate, but Markdown Output Builder only formats that checklist as ordered Markdown. You run the checks yourself in production and trigger any rollback through your own deploy tooling.
What goes in the INPUT section before generating the smoke test?
Describe what shipped and the critical paths it could affect, which the template collects under INPUT as "[What shipped and the critical paths it could affect]." That single description drives the CRITICAL PATHS list and the per-path CHECK criteria, so a vague input yields a vague checklist rather than the login, checkout, and core-action flows worth verifying.
More resources from Markdown Output Builder
Resource
README Prompt Template
Overview, Installation, Usage, Examples, Configuration — the README skeleton with required, runnable code examples.
Resource
API Documentation Prompt
Overview, Authentication, Endpoints, Error Handling, Rate Limits — endpoint docs in an identical structure, with parameter tables and runnable examples forced.
Resources that pair well
Resource
Executive Summary Prompt
Summary, Why It Matters, What Happens Next — the executive summary contract for readers who will never open the source.
Resource
Force JSON Output from AI
Stop getting 'Sure, here is the JSON…' — the output-contract pattern that forces models to return only parseable JSON: schema, example, and a strict rule block.
Resource
Fix Invalid JSON from AI
The JSON won't parse and you can't see why. Deterministic cause-sniffing — trailing commas, single quotes, unclosed brackets — and the repair prompt that fixes it.
Related tools
Tool
Markdown Output Builder
Build prompts that produce documents in a fixed structure — headings, sections, and tables.
Guides for this resource
Guide
Write a Rollback Plan With AI Before You Ship
AI deployment plans end at "roll back if needed" — no trigger, no undo steps, no flag on what can't be reversed. Here's how to write a rollback plan before you ship: a measurable trigger, the reverse of every step, the parts you can't undo, and who makes the call.
Guide
How to Write a Deployment Runbook With AI
"Bump the tag and restart — ask Priya if it breaks" is not a runbook, and Priya is on a plane. Here's how to turn what you actually do into a deployment runbook someone else can execute: preconditions, ordered steps, a verification at every gate, a failure path that isn't hope.