ai app production launch check

The problem

AI-generated prototypes and rapid-build apps often contain hidden launch blockers, such as leaked secrets, broken auth boundaries, or missing production configurations. Developers frequently move from "it works on my machine" to production without a systematic audit of security, performance, and deployment readiness.

What it does

• Inventories the tech stack, dependencies, and environment configurations across monorepos or single apps.
• Audits code for P0 blockers including exposed credentials, insecure CORS policies, and broken authorization logic.
• Performs static and runtime checks for database migration safety, API contract consistency, and N+1 query patterns.
• Generates and applies safe patches for confirmed vulnerabilities and configuration errors.
• Produces a structured production readiness report with verified vs. unverified status for every fix.

Frameworks & tools

Compatible with any stack including Node.js (Next.js, Vite), Python (FastAPI, Django), Go, Rust, .NET, and mobile frameworks like Expo or Flutter. Works with projects generated by Cursor, Bolt, Lovable, v0, and Replit.

Why this beats prompting it yourself

General-purpose prompts often miss deep architectural risks like race conditions in migrations or server-side secrets leaking into client bundles. This skill follows a rigorous DISCOVER-to-VERIFY loop that demands evidence for every finding, ensuring you don't get generic advice or hallucinated security fixes.

Use cases

• Hardening a Bolt or v0 generated prototype for its first real-world users.
• Pre-deployment security audit for a TypeScript monorepo.
• Fixing environment-specific bugs that only appear in production build artifacts.
• Verifying database migration safety before a high-traffic release.

Known limitations

Cannot verify runtime behavior if shell/terminal access is unavailable. Does not automatically rotate production credentials or perform destructive infrastructure changes.