What problem does it solve? Product teams building algorithm study-group features often drift into generic community tools, shallow solved-count tracking, and leaderboards that demotivate or invite cheating. This Skill grounds group assignment, accountability, peer review, discussion, leaderboard, and mentor-dashboard decisions in established learning science so the team defines requirements that actually reinforce the problem-solving loop. ## Core Features & Use Cases - Study Group Product Review: Produces a structured review covering group context, core loop, requirements, rules, and metrics for a study-group feature. - Group Assignment Flow Design: Maps assignment frames, member states, review flow timing, and edge cases such as copied solutions and spoiler discussions. - Learning-Science Grounding: Applies Self-Determination Theory, social comparison, social loafing countermeasures, Peer Instruction, pair programming, and Goodhart's law to leaderboard, streak, and accountability design. - Use Case: A team asks whether to add a leaderboard to their algorithm study app; the Skill reframes the question around comparison framing, opt-in visibility, and gaming risks, then outputs planner-friendly requirements and validation signals. ## Quick Start Ask the Skill to define requirements and risks for a study-group feature that assigns weekly algorithm problems with peer review and a leaderboard.
