star-plan-reviser

To audit a research plan, you compare stated objectives against execution logs and disk artifacts. This evidence-based auditing cross-references project outcomes to score completion and identify discrepancies.

Evidence-based research plan revision is the structured process of updating project documentation to match experimental outcomes. You need it after running experiments to prevent documentation drift and maintain auditability.

You update research plan files through a structured, user-approved revision process. This ensures consistency across the project tree by aligning strategic pivots and new findings with existing workflow conventions.

Yes, the STAR workflow supports automated plan auditing through integrated conventions. It cross-references execution evidence to ensure documentation remains accurate and aligned with experimental outcomes.

Yes, you can use this auditing approach for reproducibility documentation. By comparing research plans against actual execution logs and disk artifacts, it ensures project documentation maintains evidence-based auditability.

Manual research plan revisions risk documentation drift and project tree inconsistency. Automated evidence-based auditing prevents this by cross-referencing execution logs to ensure updates remain aligned with actual artifacts.