Production Readiness (Developer)

The problem

AI-assisted development tools like Cursor, Bolt, and Lovable are excellent at building functional prototypes fast, but they often ignore the critical infrastructure required for real users. Shipping a "vibe-coded" app without hardening results in data leaks, broken payment flows, and unexpected API bills.

What it does

• Identifies missing production requirements across 14 categories including auth, databases, security, and billing.
• Conducts evidence-based audits by scanning your repository for hardcoded secrets, insecure token storage, and unvalidated trust boundaries.
• Enforces best practices for LLM integrations, specifically targeting cost protection and rate limiting to prevent budget exhaustion.
• Scales recommendations based on app maturity, from private beta requirements to high-scale performance tuning.

Frameworks & tools

Stack-agnostic by design. The evidence checks — hardcoded secrets, migration history, webhook signature verification, CI config, rate-limited auth — target patterns common to any full-stack web app, not one vendor's stack. Works whether you're on Node.js, Python, Ruby, or Go, with any SQL database or payment processor.

Why this beats prompting it yourself

Generic prompts often result in a "lecture" on best practices rather than actionable fixes. This skill uses a strict evidence-first approach, verifying your actual code against a professional checklist instead of asking you questions you might not know the answers to.

Use cases

• Audit a prototype before opening it to paying customers.
• Harden an AI-generated codebase against common security vulnerabilities.
• Configure cost guardrails for LLM-backed features to prevent abuse.
• Identify performance bottlenecks like N+1 queries or missing database indexes.

Known limitations

Full Audit Mode benefits from repository access to cite real file:line evidence; without it, the skill still works as passive reference guidance. Recommendations scale with app stage, so it won't suggest enterprise-grade load balancing for a simple MVP.

Built by Super Logic AI

Free, open source, MIT-licensed. Built by Super Logic AI — production AI automation for real businesses. Source and updates live on GitHub — if this saves you a production incident, a star on the repo helps others find it.