Planning has emerged as one of the most crucial features of agentic workflows -- planning is what turns simple order-takers into complex agentic systems. However, these plans must be intelligible to humans, and capable of being interacted with. We examine a very specific scenario: research planning, i.e. the process of creating a structured approach to a scientific problem, and adjudication/refinement through a rubric initially hidden from the planner. The green agent plays the role of the adjudicator (think thesis supervisor, just less grumpy): it evaluates purple's submission according to a preset rubric and returns feedback. Reward is calculated contingent on performance. The overriding purpose is for the agent to discover the rubrics themselves to as wide an extent as possible. For this reason, these are gradually disclosed to the purple agent, but with 'stakes' -- progressive disclosure also increases the penalty from a disclosed item the agent fails to respond to.