Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
Use when creating or developing anything, before writing code or implementation plans - refines rough ideas into fully-formed designs through structured Socratic questioning, alternative exploration, and incremental validation
Force unrelated concepts together to discover emergent properties - "What if we treated X like Y?"
Use when tests have race conditions, timing dependencies, or inconsistent pass/fail behavior - replaces arbitrary timeouts with condition polling to wait for actual state changes, eliminating flaky tests from timing guesses
Use when invalid data causes failures deep in execution, requiring validation at multiple system layers - validates at every layer data passes through to make bugs structurally impossible
Use when partner provides a complete implementation plan to execute in controlled batches with review checkpoints - loads plan, reviews critically, executes tasks in batches, reports for review between batches
Comprehensive GitHub code review with AI-powered swarm coordination
Flip core assumptions to reveal hidden constraints and alternative approaches - "what if the opposite were true?"