AI Code Ship-Safe Pack

An adversarial senior engineer review gate that audits AI-written code for security gaps and logic errors before shipping.

Review an AI-generated code diff for the failure modes coding agents actually have — claimed-done-but-not-done, gamed or weakened tests, stubs passed off as complete, silent scope creep, hallucinated APIs, and security regressions. Returns an APPROVE or REQUEST CHANGES verdict with a completion check and severity-ranked fixes.

An adversarial reviewer for AI-written code changes. It pressure-tests a pull request or diff for untested branches, silent behavior changes, missing edge cases, over-confident code that only looks right, and weak tests, then returns a PASS / REVISE / BLOCK verdict before the change merges.

Generate a real test suite for any function, module, or file — meaningful edge cases, error paths, boundary conditions, and proper mocks, not happy-path stubs. Detects your project's framework and conventions, plans the cases deliberately before writing, and hands back runnable tests plus a summary of what's covered. Built to write the tests that actually catch bugs.

Audit your project's dependencies for supply-chain risk before they ship. Detects the ecosystem, runs the right vulnerability scanners against live advisory data, and adds the checks tooling misses — outdated or abandoned packages, typosquatted or suspicious names, risky install scripts, and license conflicts — then returns a prioritized fix list and a PASS / REVIEW / BLOCK verdict. It's npm audit with triage and judgment on top.

Review a database schema, queries, or migration for the mistakes that get expensive in production — bad table design, missing or wrong indexes, slow and N+1 queries, SQL injection, and migrations that lock or break prod. Engine-aware (PostgreSQL, MySQL, SQLite, SQL Server), it runs an ordered review and returns a PASS/REVIEW/BLOCK verdict with prioritized fixes. Schema mistakes are the most expensive kind — this catches them before they ship.

An adversarial reviewer for Dockerfiles and container builds. It flags root users, image bloat, unpinned or cache-busting layers, leaked secrets, and missing hardening, then returns a PASS / FIX / BLOCK verdict — before you build or push the image.

Turn an error, stack trace, and logs into a structured root-cause diagnosis — reconstructed failure, ranked hypotheses with evidence, the most likely cause, and the cheapest next diagnostic or fix. The disciplined pass a senior engineer runs, instead of scattershot guess-and-check.