arXiv AI
Jun 15
SkillAudit: Ground-Truth-Free Skill Evolution via Paired Trajectory Auditing
arXiv:2606. 14239v1 Announce Type: new Abstract: Agent skills are structured procedural packages that guide frozen LLM agents in specialized workflows.
SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use
arXiv:2607. 01874v1 Announce Type: new Abstract: Skills are becoming a reusable operational layer for LLM agents, encoding SOPs, domain rules, tool workflows, scripts, and validation routines.
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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
Jun 17
A Framework for Evaluating Agentic Skills at Scale
arXiv:2606. 17819v1 Announce Type: cross Abstract: Agent skills -- structured, reusable knowledge artifacts that augment LLM agent capabilities -- have been rapidly adopted in industry, yet their cross-domain impact and use across commercial and open-source models remain under-studied, and no reusable methodology exists for evaluating an individual skill.
arXiv AI
Aug 12
CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification
arXiv:2604. 01687v3 Announce Type: replace Abstract: Anthropic proposes the concept of skills for LLM agents to tackle multi-step professional tasks that simple tool invocations cannot address.
arXiv AI
Aug 7
Search2Skill: Skill Distillation Beyond Knowledge Boundaries Via Rubric-Based Reinforcement Learning
arXiv:2608. 05245v1 Announce Type: new Abstract: Reusable skills, which encapsulate the procedural knowledge required to solve real-world professional tasks, offer LLM-based agents a path toward self-evolution in expert domains.
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
Jul 23
You Live More Than Once: Towards Hierarchical Skill Meta-Evolving
arXiv:2605. 28390v2 Announce Type: replace Abstract: Test-time skill evolving is regarded as a new paradigm for enhancing deployed agentic systems.
arXiv AI
Aug 11
SkillSentry: Reliable Skill Execution for LLM Agents via Runtime Assurance
arXiv:2608. 09253v1 Announce Type: new Abstract: LLM agents are increasingly equipped with skills to perform complex tasks through multi-step reasoning and tool use.
Hugging Face Trending Papers
Aug 12
Agent Skills Can Be Harmful: An Empirical Study of Skill-Induced Failures in LLM Agents
Agent skills are the de facto mechanism for extending LLM agents with reusable guidance. A skill can shape the agent's task execution, including planning, tool use, problem-solving, and validation.
arXiv AI
Jul 7
Skill Coverage: A Test Adequacy Metric for Agent Skills
arXiv:2606. 20659v2 Announce Type: replace Abstract: Agent skills encode reusable procedural knowledge for large language model (LLM) agents, and existing benchmarks show that such skills can improve task-level performance.
arXiv AI
Jun 2
SkillSmith: Co-Evolving Skills and Tools for Self-Improving Agent Systems
arXiv:2606. 01314v1 Announce Type: new Abstract: Recent self-evolving agents have shown that skills can be discovered, refined, and accumulated through execution.
arXiv AI
6d ago
Agent Skills Can Be Harmful: An Empirical Study of Skill-Induced Failures in LLM Agents
arXiv:2608. 11888v1 Announce Type: new Abstract: Agent skills are the de facto mechanism for extending LLM agents with reusable guidance.