Possible complementary direction: long-term skill lifecycle management with SkillClaw

Hi, I'd like to suggest a complementary direction for skills.

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

Your project focuses on skills for media and developer workflows.

SkillClaw focuses on a different but related problem that shows up once skill libraries grow over time:

• duplicated skills accumulate
• older skills become stale
• skills fragment across agents, devices, and workspaces
• long-term skill quality becomes harder to manage

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 think it is complementary rather than competitive: your repo helps people create, discover, or use skills, while SkillClaw addresses skill lifecycle management after those skills have been used repeatedly.

If useful, I can put together a concise note, example workflow, or integration angle.

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