by MemTensor · Agent Tool · ★ 219
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
SkillsVote Lifecycle Governance of Agent Skills: From Collection and Recommendation to Evolution Route skills just in time, learn from task execution, and evolve reusable skill libraries through attribution-grounded feedback. Powered by MemTensor <img src=
| Stars | 219 |
| Forks | 11 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67.0212816955678/100 |
| Open Issues | 2 |
| Last Updated | 2026-05-19 |
| Created | 2026-04-03 |
| Platforms | python |
| Est. Tokens | ~336k |
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skills-vote is SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution. It is categorized as a Agent Tool with 219 GitHub stars.
skills-vote is primarily written in Python. It covers topics such as agent-skill, agent-skills, llm.
You can find installation instructions and usage details in the skills-vote GitHub repository at github.com/MemTensor/skills-vote. The project has 219 stars and 11 forks, indicating an active community.
skills-vote is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to skills-vote on Agent Skills Hub include wcgw, AgentChat, llama-cpp-agent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.