Board game design alternates between thinking as a designer and experiencing as a player, over repeated cycles of prototyping, critique, and revision. This loop is cognitively demanding: without knowing how players will receive a rule, a designer cannot tell what to revise. We present CoBG, a design assistant that supports this workflow end to end with four modules that learn from 2.2K structured rulebooks and 180K player reviews: BG-Ideator turns multi-turn dialogue into a structured design draft; BG-Realizer writes a rulebook and revises it with BG-Critic, a review-grounded critic that localizes flaws along the Mechanics-Dynamics-Aesthetics chain and accepts a revision only when it prefers it; and BG-Persona previews feedback from 150 profiled reviewers. On 207 held-out games, CoBG localizes flaws in rulebooks and revises them better than general-purpose LLMs, and iterative revision brings their rating close to that of published rulebooks. Blind readers prefer CoBG's rulebooks to GPT-5.4's in 38 of 50 new design intents under the same revision budget. In a 30-participant user study and paper-prototype playtests, designers using CoBG report less blank-page anxiety and catch flaws they would otherwise miss, and the resulting rulebooks hold up at the table with few rule breakdowns.

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