Why: AI code moves faster than your safety net

AI coding agents now write a large share of production code. They are fast and plausible — and occasionally unsafe, in the quiet way that plausible code is: it compiles, it reads fine in review, and it fails only later. Lint and CI pipelines were not designed to verify that volume, at that pace, with that kind of output.

Veylqorix fills that gap with a simple stance: verify with real scanners. Dependency auditing via npm audit and pip-audit, offline secret detection across 9 rule families, manifest-level license checks, and quality runs (TypeScript, ESLint, Ruff, test suites). Their output is normalized into a single finding schema, then judged by a deterministic policy gate.

The principle that holds it together

A scanner error, or a skipped mandatory check, degrades coverage. It is never mistaken for a clean pass. Veylqorix surfaces incomplete audits instead of green-washing them — a check that cannot run is reported SKIPPED or ERROR with a reason, and the gate reports INCOMPLETE.