AI agents have now entered the stage of large-scale enterprise adoption, and simply calling ready-made AI tools can no longer meet enterprises' personalized business needs. Most practitioners only know basic AI conversations, do not understand the underlying logic of agent skills, and cannot independently build, customize, or deploy dedicated skill modules. They are unable to solve customized scenario problems such as enterprise office work, business workflows, and automated operations and maintenance, making it difficult to commercialize and reuse AI capabilities at the enterprise level, and severely limiting their career competitiveness.

This Agent Skills Enterprise-Level Application Practicum focuses on the industry's cutting-edge modular skill system for AI agents. Starting from zero-base foundational understanding, it takes you step by step through skill principles, engineering standards, and multi-platform building methods, ultimately achieving enterprise-level deployment and operations management. The course covers hands-on operations on mainstream platforms such as Claude Code, Trae IDE, Coze Programming, CodeBuddy, Codex, and OpenClaw, giving you the complete ability to independently develop, deploy, and manage AI skill modules, making you an AI skill development talent urgently needed by enterprises.

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• 1.Why We Need Skills
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• 2.Skill Fundamentals & Engineering Definition
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• 3.Skill Runtime Environment & Core Principles
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• 4.Skill Engineering Practice Guide
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• 5.Skill Enterprise-Level Application Practicum
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• 6.Building a Skill with Claude Code
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• 7.Building a Skill with Trae IDE
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• 8.Deploying a Skill with Coze Programming
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• 9.Installing a Skill from the CodeBuddy Skill Marketplace
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• 10.Managing Project & User Skills in CodeBuddy
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• 11.Building an Enterprise-Level Skill in CodeBuddy
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• 12.Codex Skills Overview
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• 13.Building Codex Skills
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• 14.Using Codex Skills
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• 15.Building OpenClaw Skills
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• 16.Using OpenClaw Skills
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• 17.Using the ClawHub Skill Store
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💡 Learning Tip: Tutorial content is based on industry practices at time of publication; please verify against current platform rules and adapt the methods to your own situation for best results.