audit-schema-gaps

What problem does it solve?

CultureMech can silently accept broken YAML records when validation is run in open mode or when exit codes are swallowed, causing schema drift and data quality issues to go unnoticed.

Core Features & Use Cases

• Strict instance validation with closed-schema enforcement: Validates every normalized YAML instance and flags unexpected fields so failures cannot hide.
• Schema-level probes and consistency checks: Audits identifier policies, naming divergence across term/ontology fields, requiredness inconsistencies, orphan enums, and broken range references.
• Pipeline/writer assurance audit: Scans modules that write YAML to verify dry-run support, in-pipeline validation before writing, and whether safeguards are wired into existing just targets.
• Actionable, ranked fix backlog: Produces machine-readable and narrative reports that prioritize fixes (starting with the CI gate) to prevent regressions.

Quick Start

Run the audit by asking an AI to execute: just validate-strict, then review the generated reports under reports/ for instance failures, schema gaps, and pipeline writer issues.