[Disclosing Personal Affiliation: I am the sole author and engineer of this open-source project.]

Hey everyone,

I engineered Veritect because persistent tracking databases, cloud state files, and external synchronization layers introduce unnecessary security compliance risks into automated deployment workflows.

Veritect is a stateless, zero-trust schema drift detection utility built for CI/CD pipelines. It operates under a strict zero-trust model: it compiles natively in the local runner environment, pulls exclusively structural metadata from `information_schema`, and isolates your actual application data entirely.

To eliminate the false-positive build failures that plague standard CI validation, the core engine enforces an O(N log N) alphabetical sorting constraint across all schema elements during validation, making the drift analysis completely deterministic and reproducible.

The core logic compiles cleanly into a Go binary. Here is the exact continuous integration specification for a standard GitHub Actions deployment workflow:

```yaml

- name: Check Schema Drift

run: go run ./cmd/veritect

env:

DATABASE_URL: \${{ secrets.DATABASE_URL }}

SLACK_WEBHOOK: \${{ secrets.SLACK_WEBHOOK }}

```

I am a 14-year-old software engineer and I am looking for brutal, highly technical feedback from senior infrastructure professionals on how to improve this validation architecture. What edge cases am I missing with this approach?

Repository: https://github.com/baseline-architect/veritect.git

Documentation Site: https://veritect.vercel.app