# Agent Skills: A Data-Driven Analysis of Claude Skills for Extending Large Language Model Functionality arXiv: https://arxiv.org/abs/2602.08004 ยท HTML: https://mlsanity.com/paper/2602.08004/ ## Key facts - Cited by 72 papers in the map (data through 14 Oct 2026). - Placed in Agent skill learning and evolution, one of 16 directions in LLM agents and tool use. - Builds on 7 of its 19 references that are in the map. - First posted on arXiv 8 Feb 2026. ## Placed in - LLM agents and tool use / [Agent skill learning and evolution](https://mlsanity.com/agents/agent-skill-learning-and-evolution/) ## Builds on (most cited first, 7 of 7) - [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022) - [A Survey on Large Language Model based Autonomous Agents](https://mlsanity.com/paper/2308.11432/) (2023) - [Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale](https://mlsanity.com/paper/2601.10338/) (2026) - [Agent Skills Enable a New Class of Realistic and Trivially Simple Prompt Injections](https://mlsanity.com/paper/2510.26328/) (2025) - [What Generative Search Engines Like and How to Optimize Web Content Cooperatively](https://mlsanity.com/paper/2510.11438/) (2025) - [ReUseIt: Synthesizing Reusable AI Agent Workflows for Web Automation](https://mlsanity.com/paper/2510.14308/) (2025) - [A Large-Scale Study on the Development and Issues of Multi-Agent AI Systems](https://mlsanity.com/paper/2601.07136/) (2026) ## Built on by (most cited first, 30 of 72) - [Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering](https://mlsanity.com/paper/2604.08224/) (2026) - [Organizing, Orchestrating, and Benchmarking Agent Skills at Ecosystem Scale](https://mlsanity.com/paper/2603.02176/) (2026) - [SkillLearnBench: Benchmarking Continual Learning Methods for Agent Skill Generation on Real-World Tasks](https://mlsanity.com/paper/2604.20087/) (2026) - [SkillNet: Create, Evaluate, and Connect AI Skills](https://mlsanity.com/paper/2603.04448/) (2026) - [SkillOS: Learning Skill Curation for Self-Evolving Agents](https://mlsanity.com/paper/2605.06614/) (2026) - [Skill Retrieval Augmentation for Agentic AI](https://mlsanity.com/paper/2604.24594/) (2026) - [SkillAttack: Automated Red Teaming of Agent Skills through Attack Path Refinement](https://mlsanity.com/paper/2604.04989/) (2026) - [SkillJect: Effectively Automating Skill-Based Prompt Injection for Skill-Enabled Agents](https://mlsanity.com/paper/2602.14211/) (2026) - [SkillSafetyBench: Evaluating Agent Safety under Skill-Facing Attack Surfaces](https://mlsanity.com/paper/2605.12015/) (2026) - [SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution](https://mlsanity.com/paper/2605.18401/) (2026) - [CODESKILL: Learning Self-Evolving Skills for Coding Agents](https://mlsanity.com/paper/2605.25430/) (2026) - [Context Matters: Repository-Aware Security Analysis of the Agent Skill Ecosystem](https://mlsanity.com/paper/2603.16572/) (2026) - [HarmfulSkillBench: How Do Harmful Skills Weaponize Your Agents?](https://mlsanity.com/paper/2604.15415/) (2026) - [Cloak and Detonate: Scanner Evasion and Dynamic Detection of Agent Skill Malware](https://mlsanity.com/paper/2607.02357/) (2026) - [Skill Self-Play: Pushing the Frontier of LLM Capability with Co-Evolving Skills](https://mlsanity.com/paper/2607.22529/) (2026) - [Skill-Use: Can LLMs Actually Use Skills in Agentic Harnesses?](https://mlsanity.com/paper/2608.04828/) (2026) - [Skill0.5: Joint Skill Internalization and Utilization for Out-of-Distribution Generalization in Agentic Reinforcement Learning](https://mlsanity.com/paper/2605.28424/) (2026) - [Skill Coverage: A Test Adequacy Metric for Agent Skills](https://mlsanity.com/paper/2606.20659/) (2026) - [SkillHone: A Harness for Continual Agent Skill Evolution Through Persistent Decision History](https://mlsanity.com/paper/2606.08671/) (2026) - [SkillGuard: A Permission-Centric Framework for Agent Skill Security](https://mlsanity.com/paper/2606.03024/) (2026) - [FederatedSkill: Federated Learning for Agentic Skill Evolution](https://mlsanity.com/paper/2606.03143/) (2026) - [From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI](https://mlsanity.com/paper/2606.14502/) (2026) - [From Anatomy to Smells: An Empirical Study of SKILL.md in Agent Skills](https://mlsanity.com/paper/2607.01456/) (2026) - [Dynamic Agent Skills: A Lifecycle Survey and Taxonomy of Evolving Skill Libraries](https://mlsanity.com/paper/2607.10113/) (2026) - [Red Skills or Blue Skills? A Dive Into Skills Published on ClawHub](https://mlsanity.com/paper/2604.13064/) (2026) - [Seeing Is Not Screening: Multimodal Hidden Instruction Attacks on Agent Skill Scanners](https://mlsanity.com/paper/2606.18198/) (2026) - [SkillComposer: Learning to Evolve Agent Skills for Specification and Generalization](https://mlsanity.com/paper/2606.06079/) (2026) - [Living-Harness Is an Interactive-Agent Evolver](https://mlsanity.com/paper/2607.26598/) (2026) - [ColluSkill: Adversarial Cross-Skill Composition for Evading Agent Skill Scanners](https://mlsanity.com/paper/2608.09732/) (2026) - [COLLEAGUE.SKILL: Automated AI Skill Generation via Expert Knowledge Distillation](https://mlsanity.com/paper/2605.31264/) (2026) ## Abstract (arXiv) Agent skills extend large language model (LLM) agents with reusable, program-like modules that define triggering conditions, procedural logic, and tool interactions. As these skills proliferate in public marketplaces, it is unclear what types are available, how users adopt them, and what risks they pose. To answer these questions, we conduct a large-scale, data-driven analysis of 40,285 publicly listed skills from a major marketplace. Our results show that skill publication tends to occur in short bursts that track shifts in community attention. We also find that skill content is highly concentrated in software engineering workflows, while information retrieval and content creation account for a substantial share of adoption. Beyond content trends, we uncover a pronounced supply-demand imbalance across categories, and we show that most skills remain within typical prompt budgets despite a heavy-tailed length distribution. Finally, we observe strong ecosystem homogeneity, with widespread intent-level redundancy, and we identify non-trivial safety risks, including skills that enable state-changing or system-level actions. Overall, our findings provide a quantitative snapshot of agent skills as an emerging infrastructure layer for agents and inform future work on skill reuse, standardization, and safety-aware design.