skill-creation

Hermes Agent by Nous Research introduces /learn, a command that lets the agent deliberately create skills from documentation, code, or instructions without needing to first fail at the task, turning any source into a reusable skill.

This paper introduces W2S, a framework that automatically constructs executable Skills for LLM agents from historical interaction traces using a Skill-IR intermediate representation, improving behavioral replay consistency by 10.5% over baselines.

MUSE-Autoskill proposes a skill-centric agent framework that enables LLM agents to continuously create, reuse, and refine skills through a unified lifecycle of creation, memory, management, evaluation, and refinement. Experiments on SkillsBench show that lifecycle-managed skills improve task success, efficiency, reuse, and cross-agent transfer.

The author released 'Skill Factory', a meta-skill for OpenClaw that provides a structured workflow for creating, iterating, and publishing skills, aiming to improve transparency and ease of construction.