A Survey of Agent Skills for Foundation-Model Agents: Concepts, Representations, Lifecycles, Evaluation, and Applications

Foundation-model agents now use reusable skills for tool use, long-horizon planning, and adaptation across related tasks. The term, however, is used loosely. It may describe a prompt package, an executable workflow, a learned routine, or an artifact distributed through a repository. That looseness makes it hard to compare methods, measure progress, or discuss security and governance with precision.We study agent skills as reusable and adaptive units of competence between model capability and situated task execution. The survey separates skills from nearby constructs such as prompts, tools, memory, and policies, then organizes the literature around representation, lifecycle and orchestration, evaluation, security and governance, and application domains. Across these areas, skill quality is only one part of the story. Useful skills also depend on abstraction choices, retrieval and composition mechanisms, ecosystem structure, and infrastructure security. We treat agent skills as a research object in their own right and identify open problems in automatic induction, cross-environment transfer, longitudinal evaluation, and trustworthy sharing in open agent ecosystems. A public paper list is available at https://github.com/JinhaoShen/awesome-agent-skill-papers.