Waveframe-Stamp: A Deterministic Metadata Diagnostics and Remediation Engine

Waveframe-Stamp is a deterministic metadata validation and diagnostics engine designed to support governed, reproducible research workflows. It validates artifact metadata against explicit schemas, emits stable and structured diagnostics describing factual schema violations, and generates conservative fix proposals and human-action remediation summaries without performing enforcement or policy interpretation. Unlike traditional linters or validators, Stamp enforces a strict separation between validation, remediation, and judgment. All validation results are normalized into Canonical Diagnostic Objects (CDOs) with stable semantic identifiers, making diagnostics diffable, loggable, and suitable for automation, UI presentation, and long-term audit. Fix proposals are generated deterministically as claims rather than actions, and automated mutation is limited to explicitly safe, mechanical transformations. Stamp is schema-agnostic, policy-neutral, and format-flexible, supporting Markdown frontmatter and embedded code metadata. It emits JSON-first CLI output and produces immutable execution trace artifacts for provenance and enforcement systems. Stamp is intended as a foundational "front door" to governed research ecosystems and serves as an upstream dependency for enforcement layers such as CRI-CORE.