What problem does it solve? It removes ambiguity between idea generation and theorem proving by translating an approved branch-local research idea into a precise mathematical setting and goal, so proof stages can start without redefining the problem or guessing missing assumptions. ## Core Features & Use Cases - Theorem-Ready Formalization: Converts idea.md into a structured setting.md with a Basic setup, Technical assumptions carrying stable assump:<slug> ids, and a single Goal statement. - Failure-Driven Revision Support: Preserves previously valid formalization choices after controller-level idea modification, applying only the approved semantic delta from the recorded failure. - Assumption Discipline: Distinguishes primitive checkable assumptions from derived properties, routing unsupported theorem-critical assumptions back to idea generation instead of adding them silently. - Use Case: In an ML theory research workflow, after a perspective branch's idea is approved, run this skill to produce perspective_M/idea_N/setting.md that downstream proof-sketch stages can consume directly. ## Quick Start Formalize the approved idea in perspective_1/idea_2/idea.md into a theorem-ready setting.md following the shared template.