reflexion:memorize

You aggregate reflection and critique outputs into CLAUDE.md by applying an ACE grow-and-refine workflow that captures high-signal insights as atomic, evidence-backed bullets with explicit context for durable knowledge retention.

Building an evolving knowledge base requires aggregating critique outputs into a structured context playbook using targeted section updates and dry-run previews, ensuring incremental memory growth while preventing context collapse.

Yes, you can execute dry-run previews to inspect how recent reflections will update CLAUDE.md, allowing you to validate evidence-backed, atomic bullets and cross-references before applying any permanent changes to the knowledge base.

Memorizing reflections ensures privacy and prevents context collapse by applying defined quality gates, structured templates, and targeted section updates that validate memory and maintain atomic, action-oriented insights within the evolving CLAUDE.md file.

You need to apply quality gates during memory validation when updating CLAUDE.md with new critique outputs, ensuring every captured insight remains evidence-backed, atomic, and privacy-safe before it enters your durable, evolving knowledge base.