three-stage-eval

A three-stage evaluation pipeline verifies code against a seed specification by running mechanical syntax checks, mapping outputs to acceptance criteria for semantic scoring, and triggering multi-perspective consensus review on borderline scores.

To enforce pre-merge verification for infrastructure configurations, evaluate the implemented artifacts against a seed specification file to generate deterministic mechanical PASS/FAIL results and quantitative semantic drift metrics before deployment.

Semantic drift evaluation in release gating quantifies how far artifact outputs deviate from acceptance criteria. It computes compliance scores and triggers a multi-perspective consensus review when drift metrics are high.

Yes, you can use consensus review for high-stakes code reviews. When semantic evaluation scores are borderline, it triggers a multi-perspective deliberation involving a Proposer, Devil's Advocate, and Synthesizer to reach a 2/3 decision.

Mechanical checks for agent output evaluation are limited to deterministic syntax, lint, test, and coverage validation. They cannot detect semantic mismatches or resolve high-stakes disagreements, requiring subsequent semantic and consensus stages.

Yes, the three-stage-eval approach supports gap audits for software engineering artifacts by enforcing coverage thresholds and schema validation during mechanical checks, then mapping outputs to acceptance criteria to quantify semantic drift.