COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation 📗 Read #Shorts

This paper takes on agent skills — the reusable packages that make AI agents bounded experts in specific roles or people.

Today's options fragment the problem: memory captures fragments, persona handles style, skill formats provide packaging. None of them turn raw expert traces into an inspectable skill end-to-end.

COLLEAGUE.SKILL is trace-to-skill distillation. Feed it materials from a person or role, out comes a versioned skill with two tracks — capabilities and bounded behavior. You inspect, correct via natural language, roll back, deploy across agent hosts.

Eighteen thousand stars and over two hundred contributed skills. Open source today.

Verdict: Read.
🔗 https://arxiv.org/abs/2605.31264
👥 Tianyi Zhou, Dongrui Liu, Leitao Yuan +2
📂 cs.AI · 📅 2026-05-29 · ⬆ 66 on HF Daily Papers
📗 PaperCut verdict — Read: Distill an expert into a portable skill.

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