arXiv AI
Who Maintains Agent Skills? A Longitudinal Study of Human-Governed, AI-Assisted Skill Maintenance
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arXiv AI
Aug 7
SkillTrace: Multi-Trace Provenance Auditing for LLM-Agent Skill Reuse
arXiv:2608. 05204v1 Announce Type: new Abstract: LLM-agent ecosystems are rapidly growing around reusable skills: mixed-modality packages of metadata, natural-language instructions, code, tools, references, and operational workflows.
arXiv AI
Jul 14
Dynamic Agent Skills: A Lifecycle Survey and Taxonomy of Evolving Skill Libraries
arXiv:2607. 10113v1 Announce Type: new Abstract: Large language model agents increasingly store reusable procedures outside the model.
arXiv AI
Jun 16
SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution
arXiv:2605. 18401v2 Announce Type: replace-cross Abstract: Long-horizon LLM agents generate traces that could become reusable experience, but raw trajectories are noisy, local, and hard to govern.
arXiv AI
23h ago
When Skills Tell Agents Not to Ask: A Large-Scale Study of Oversight Directives in Agent Skills
The paper investigates oversight‑loosening directives embedded in AI agent skills—reusable instruction packages centered on a SKILL.md file. Analyzing 1.53 million English skills from GitSkills, the authors find that roughly one in seventeen skills (about 88,000) contains a directive that bypasses checks or approvals, often via permission flags and applied unconditionally. The study shows that such directives cluster in a small number of upstream skills and that current open‑source scanners miss most of them, while an LLM‑based detector performs better.
arXiv AI
Jun 2
SkillRevise: Improving LLM-Authored Agent Skills via Trace-Conditioned Skill Revision
arXiv:2606. 01139v1 Announce Type: new Abstract: Agent skills are procedural artifacts that enable LLM agents to execute workflows, verify constraints, and recover from failures.
arXiv AI
Sep 3
Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills
The paper introduces Repo-To-Skill, a method for converting GitHub repositories into reusable AI skills. By distilling operational knowledge from over 1,000 machine‑learning repositories, the authors build the AREX‑Skill Library with more than 5,000 verified skills across 20 areas. Integrating these skills into a research agent—DisCo—yields significant performance boosts on multiple benchmarks, demonstrating the value of reusable, task‑agnostic knowledge.