论文精选

Skill++ 论文:用重写技能描述解决 Agent 技能路由冲突

精选理由

给做 Agent 的朋友:往技能库里加新技能经常把旧技能路由搞坏,这篇 Skill++ 只改描述就解决了,76.3% 对 36.4% 的差距很说明问题。

Skill++ 是一篇关于 Agent 技能库维护的论文。它只重写每个新技能的名称和描述,说明该技能支持什么、与最接近的现有技能有何区别、排除什么,无需路由器训练和标注数据。技能库增长到 731 个技能、经历十轮会话后,路由器对 76.3% 的查询能选对所有需要的技能,而使用原始元数据时只有 36.4%。替换错误几乎消失,拥挤错误减半,效果在 3 个基准和 5 个路由器上成立,并延续到 Codex CLI 环境。

原文 · elvis

Good research on maintaining and scaling agent skills. DAIR.AI @dair_ai Great paper on scaling agent skills. It includes some great tips for keeping your agent skill library updated and running smoothly. (bookmark it) You will often see that adding a new skill to an agent can break routing for older skills, even when nothing about the older skills or the router changed. Routers pick skills by name and description. When a new skill has similar metadata, it can replace or crowd out an earlier one. Skill++ rewrites only the name and description of each incoming skill. The new description says what the skill supports, how it differs from its closest existing skill, and what it excludes. There is no router training and no labeled data. As a library grows to 731 skills over ten sessions, the router selects every required skill for 76.3% of queries, against 36.4% with the original metadata. Substitution errors nearly disappear, and crowding errors fall by half. The gains hold across three benchmarks and five routers, and they carry over to the Codex CLI harness. When you add a skill, describe how it differs from the closest skill you already have. Paper: arxiv.org/abs/2611.00544 Chat with Paper: academy.dair.ai/papers/skill-t… 🔗 View Quoted Tweet 💬 8 🔄 1 ❤️ 22 👀 3506 📊 11 ⚡