Knowledge Action Unity Learning Assistant

Problem: Subject learning often stays at the concept level

Many subject assistants only explain concepts or generate questions, without a clear mechanism for applying knowledge in real scenarios. Users may receive an explanation but still not know when to use it, how to combine skills, or how to verify that they can actually perform the task.

How it works: study assistant + application assistant

The skill generates two coordinated roles around a learn-then-apply loop:
- Subject study assistant: after confirming subject, grade, and learning goal, it organizes the knowledge system, plans a learning path, and defines teaching strategies. Outputs include concept explanations, exercise guidance, and learner analysis.
- Subject application assistant: converts knowledge into actionable skills, then generates skill cards, scenario matching, practical simulations, and capability certification.
Key steps include collecting subject information, designing the assistant persona, reading the relevant subject knowledge map, choosing teaching methods, generating configuration, and validating the result. On the application side, it uses an RIA-TV++ style distillation process, cross-domain validation, predictive validation, uniqueness validation, and categorization by difficulty, frequency, and subject.

Boundaries and notes

It is best suited for engineers, teachers, or learners who need structured learning paths, role-based instruction, or knowledge application simulation. The skill reads only the relevant references/ files when needed to keep context concise. If the subject goal is unclear, define grade level, module, and evaluation method first, otherwise the generated path may remain generic.