quality-validation

Quality validation enforces mandatory checkpoints by scoring ResearchPacks and Implementation Plans against objective rubrics—API/Library, Philosophy, and Pattern Research—blocking progression if outputs fall below defined thresholds like 80/100, ensuring standards are met before advancing workflow phases.

Quality validation categorizes defects as critical, major, or minor, provides detailed scores on completeness and accuracy, and surfaces actionable recommendations for refinement, preventing flawed information from propagating into implementation.

Run quality validation at ResearchPack completion, during Implementation Plan development, on explicit quality-check requests, and before transitioning to the next workflow phase to prevent garbage-in-garbage-out scenarios.

Quality validation applies standardized API/Library, Philosophy, and Pattern Research rubrics that provide measurable scoring criteria, enabling consistent, objective assessment of research and plan quality across different contexts and validation points.

Yes, quality validation enforces automated quality gates that block progression when ResearchPacks or Implementation Plans fail to meet defined quality thresholds, forcing refinement before moving forward.