Provides a 'reflect' tool that creates cognitive checkpoints for AI assistants, forcing structured step-by-step reasoning through complex problems to improve accuracy and maintain context during task execution.
Protocol-enforced learning system combining memory-augmented reasoning with workflow automation to improve AI assistant reliability by ensuring they learn from past experiences before making code changes.
Enables LLMs to break down reasoning into an explicit, editable graph of thinking steps, with visualizations and the ability to revise individual steps.
Enables LLM-driven tool execution with policy-gated authorization, deterministic verification, and replay for radiographic measurement and SQL repair tasks.
