Alibaba's Qwen Team's new paper. Skill Self-Play turns agent skills into a training-time curriculum engine.

Attacks a crucial problem： when an AI creates its own training tasks， it either stays inside narrow， easy-to-check environments or generates lots of bad and unreliable tasks.

Their solution is a growing "skill library" that tells the AI what kinds of tasks to create， how to create them correctly， and how to verify them.

These skills are used to generate better training data， not mainly to help the model answer questions.

So the whole idea is： let the model improve itself through an evolving collection of verified task templates， instead of training on uncontrolled self-generated data.