Good research on maintaining and scaling agent skills.
Skill++ rewrites agent skill metadata to fix router selection errors
AISkill++ rewrites only the name and description of each new agent skill to say what it supports, how it differs from its closest existing skill, and what it excludes. The method needs no router training or labeled data.
elvisVerified on X
@omarsar0
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: https://arxiv.org/abs/2611.00544 Chat with Paper: https://academy.dair.ai/papers/skill-towards-lifelong-agents-via-routing-aware-skill-refinement-2611.00544
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elvis · x.comPublished · added here
Original title: Good research on maintaining and scaling agent skills.