Possible complementary direction: post-task skill lifecycle management with SkillClaw

Hi, I'm reaching out because `moltworker` sits close to agent runtime and orchestration infrastructure.

Project:
https://github.com/AMAP-ML/SkillClaw

This is not meant as a generic wrapper pitch. SkillClaw focuses on a narrower ecosystem gap: after repeated usage, long-lived skill libraries often become noisy, duplicated, stale, and fragmented across agents or devices.

Its role is a post-task skill evolution loop that:

- deduplicates overlapping skills
- merges related skills
- improves skill quality over time
- shares evolved skills across agents / devices / teams

I thought this might be relevant as a complementary layer because your project already sits near the core runtime / workflow surface.

If useful, I can send a concise technical summary instead of promo copy.

Paper:
https://arxiv.org/abs/2604.08377