skilltraining-project/skill-training is a Python repository that trains an agent's skill library rather than model weights. According to the published description and the README, it corrupts part of a finished human-made work, has the agent restore it, and then updates a bundle of technique cards that can read and fix content based on the differences between the original and the result. Release information could not be confirmed.
This procedure changes document-style skills instead of retraining the model itself. Changes to the cards are kept in version control history. The README explains that after learning with professional short-drama works, it evaluates six writing metrics over multiple episodes on unseen works. The repository provides Python entry points that carry out the prepare, corrupt, restore, compare and update stages, along with installation and test procedures. So the published example is a skill-update procedure applied to writing tasks.
The scope of the evaluation is limited to the short dramas and writing metrics listed in the README. Whether the same approach is effective for other kinds of agent tasks cannot be judged from this information alone. The license field is NOASSERTION, and no grounds for confirming the terms of use were given. So it is more accurate to view this repository as a reference implementation that publishes a concrete procedure for updating document-style skills together with a limited writing evaluation, rather than a learning method with proven general performance.