Code Review Prompt — the Review Contract
"Review this code" gets shallow comments. The review contract gets findings with severities, a checklist, and a verdict.
SHIP or DO NOT SHIP: twelve checks on failure modes, observability, rollback, and load — the review that happens before the incident.
The strongest combination on the tool: Production Readiness focus under Production Gate style. Every finding answers one standing question — would this survive production traffic, failures, and attackers? — across twelve checks: timeouts and bounded retries, 3-a.m. debuggability, metrics for new behavior, environment-safe config, graceful degradation, feature-flag rollback, migration compatibility, resource limits, idempotency under retry, alarms for new failure modes, secret storage, and behavior at 10× traffic. The verdict is a deployment decision: SHIP or DO NOT SHIP, with the minimal change list that flips it.
Run it as the last gate
After correctness review, after tests — this pass asks the questions that only matter in production.
Respect the DO NOT SHIP list
The verdict comes with the minimal set of changes that would flip it — that list IS the pre-deploy task list.
Re-run at 10× growth
The traffic question ages: what survived launch traffic may not survive this quarter's.
Treat it as a structured recommendation, not a clearance. The code-review-prompt-generator outputs a prompt whose FINAL VERDICT ends in SHIP or DO NOT SHIP with a minimal-change list, but you run that prompt in your own assistant and the verdict reflects only the pasted PR and the model's findings. A human still owns the deploy decision.
It reviews the code's worst day rather than its logic. The REVIEW CHECKLIST asks production-only questions no correctness pass covers: bounded retries and timeouts, 3 a.m. debuggability without a debugger, feature-flag rollback, idempotency under retry, and what breaks first at 10x traffic. Run correctness review first; this is meant to be the last gate before deploy.
Paste a full pull request at the CODE TO REVIEW marker, since REVIEW SCOPE judges the change as it will land across files at deploy time. It expects the deploy-time diff, not a single function, so checks like migration compatibility, partial-deploy ordering, and 10x-traffic behavior have the cross-file context they need.
So the DO NOT SHIP verdict rests on ranked evidence, not vibes. The SEVERITY RULES force exactly one tag per finding by impact, not effort — CRITICAL means fix before merge, NIT is optional style. The prompt also treats missing failure handling and missing observability as findings, not nice-to-haves, so they can't quietly slip under the bar.
"Review this code" gets shallow comments. The review contract gets findings with severities, a checklist, and a verdict.
Twelve security checks — injection, auth, secrets, SSRF, privilege escalation — reviewed the way an attacker would read the code.
Architecture review for the public surface: abstractions that earn their place, dependency direction, seams, and the patterns the codebase already has.
"Refactor this code" invites silent behavior changes. The refactoring contract preserves business rules, outputs, and side effects — and flags uncertainty instead of deciding it.
getByRole over CSS chains, auto-wait over sleep, web-first assertions — Playwright tests written the way Playwright wants.
A side-by-side way to decide between two ChatGPT prompt drafts — scored on clarity, specificity, output control, and risk instead of gut feeling.
Generate code review prompts for any scope — snippet, file, diff, or full pull request — with focused review rules.
The full path from idea to a shipped SaaS MVP — define and scope the requirements, design the architecture, API, and data model, then build it reviewed, tested, secured, cost-controlled, and deployed.
The full path to an AI document processing system — define the use case, design the intake pipeline, extract fields from unstructured documents, classify and route them, pin the output contract, evaluate accuracy, then ship it monitored.
The full path to an AI content moderation system — define the policy and label taxonomy, extract signals from user content, classify it against policy, emit structured decisions, evaluate false positives and negatives, wire enforcement and review queues, review abuse risks, then ship.
The full path to a backend you can put clients on — define the requirements, design the architecture, API contract, data model, and access control, then build it reviewed, tested, secured, and shipped.
The full path to a business website that holds together — plan the content, structure the site, design the components, write the page copy, then ship it as one coherent whole.
The full path to taming an inherited codebase — understand it, document its architecture, pin its behavior with tests, then refactor, modernize, review, speed up, and ship it without breaking what works.
The full path to docs people can actually navigate — plan the doc set, structure the site, write the guides and the API reference, then ship it as a coherent documentation site.
The full path to automation that survives the real world — wire the integrations and triggers, design the control API, move the data through validated stages, evaluate the AI steps, then deploy.
The full path to a support operation, not just a bot — stand up the knowledge base, route the tickets, add the AI agent, integrate your stack, close the feedback loop, evaluate, and deploy.
The full path to an applicant tracking system — model jobs, candidates, and hiring stages, generate job descriptions and screening prompts, parse résumés into structured data, design the hiring API, set roles, review security, then ship.
The full path to a booking and reservation system — model resources, availability, and reservations, design the booking API, set customer accounts, wire calendar and notification integrations, design the UI, review security, then ship.
The full path to an inventory management system — model products, stock, locations, and movements, design the inventory API, set roles, plan supplier and POS integrations, design the UI, review data-integrity risks, then ship.
The full path to an internal admin panel — model the operational data it manages, design the management API, define RBAC and admin permissions, design the tables and forms, review risky admin actions, then ship to trusted internal users.
The full path to knowledge that's findable by people and AI — plan the taxonomy, structure it for search, write the articles, tag the metadata, make it retrievable, then ship it maintainable.
The full path to a two-sided platform — define the buyer-and-seller requirements, model the data, design the API, build roles and permissions, wire integrations, design the UI, then test, secure, and ship it.
The full path to a CRM that fits your sales process — define the contacts, deals, and pipeline, model the data that ties them together, then build the roles, integrations, and pipeline UI, and ship.
The full path to a store you own end to end — model the catalog and orders, design the storefront and checkout, add customer accounts and payments, then secure it, test it, and ship.
The full path to a pipeline that moves data without corrupting it — design the ingestion and transforms, extract and structure the sources, gate the quality, store it, then deliver and ship it monitored.
Cross the gap between 'tests pass' and 'safe in production' — assess release readiness, plan the deploy and its rollback, and set up the monitoring and launch checks before you ship, not after.
The plan AI hands you reads clean and complete — until you try to execute it and hit the missing rollback, the unnamed owner, the decision nobody made. Here's how to run a separate gap-review pass that surfaces what's missing, risky, or unclear before you act on it.
AI hands you a clean recommendation that reads as ready to use — and never shows you which assumption breaks it, which edge case sinks it, or what needs a human's eyes. Here's how to run a separate risk pass on an answer before you accept it.
Turn "are we good for Thursday?" into a checklist that can answer it — every item carrying the evidence behind it, a name, and an honest status, so the ship decision rests on what somebody checked rather than what nobody objected to.