This implements a structured hypothesis evaluation framework that moves ideas through stages of logical verification, evidence validation, and trust auditing before making a decision. You feed it a problem statement and it orchestrates multiple Claude agents in parallel to generate competing hypotheses, then progressively filters them through L0, L1, and L2 directories based on whether they pass each gate. Everything lands in a .fpf folder with markdown files tracking context, evidence, and a final decision rationale record. It's heavy process for sure, but if you're making architecture decisions or debugging complex system issues where you need to explicitly compare multiple explanations and document why you picked one, the formality actually helps. The parallel agent execution for verification steps is clever.
npx skills add https://github.com/neolabhq/context-engineering-kit --skill propose-hypotheses