GitHub 实战指南：构建一次即可在任何智能体上运行的 Agent Skills
Build once, run on any agent: A practical guide to agent skills
GitHub 官方这篇教程讲清了 Agent Skills 的写法和分层思路：工作流写成文件复用，工具和权限留在宿主侧。如果你在 Copilot 或其他智能体上重复做同类任务，照着做一次就能到处跑。
GitHub 发布一篇实战指南，讲解如何用 Agent Skills 把可重复的工程工作沉淀为文件。Skills 以文件形式存在，团队可以像代码一样审查和复用这些文件。
文章区分了三类内容的归属：skills 负责封装可复用的工作流程与知识，而工具调用、项目上下文和权限设置则保留在运行它的宿主（host）侧，例如 GitHub Copilot。这种分层让同一份 skill 无需修改就能在不同智能体环境中运行。
对维护多个智能体工作流的团队来说，这套方法减少了对单一厂商工具的绑定，开发者可以把积累的工程经验写成 skills，在不同宿主间迁移和复用。
Build once, run on any agent: A practical guide to agent skills
Agent skills capture repeatable engineering work in files teams can review and reuse, while tools, project context, and permissions remain specific to the host that runs them. The post Build once, run on any agent: A practical guide to agent skills appeared first on The GitHub Blog .
This report is categorized under AITOP's "How-to" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include GitHub Copilot, Agent Skills, 智能体, 开发者工具.
Primary source verification: published directly by GitHub Blog with first-party authority.
