爆火的Skills如何给大模型加入“技能”？记者实测

Core Concept - The emergence of "Skills" in AI represents a paradigm shift, allowing users to encapsulate specific tasks into callable modules, enhancing the functionality of large models in practical applications [1][2]. Group 1: Understanding Skills - Skills address the limitation of general AI, which can understand concepts but struggles with practical execution due to the scattered nature of operational knowledge [2][10]. - The concept originated from the AI model Claude, which introduced "Claude Skills" to enable repeatable task completion based on organizational workflows and brand standards [2][3]. - Skills can be seen as standardized modules that encapsulate multiple prompts, making it easier for users to create and utilize them without extensive programming knowledge [3][4]. Group 2: Adoption and Implementation - Major tech companies, including OpenAI, Microsoft, and Tencent, have quickly adopted the Skills framework, indicating a rapid shift in the AI landscape [4][6]. - The Skills feature was initially a niche tool but gained widespread attention and usage, with significant growth in related code repositories on platforms like GitHub [6][10]. - Users can create Skills through natural language, allowing non-programmers to develop their own modules, which has contributed to its popularity [3][10]. Group 3: Practical Applications - An example of a Skill is a "PDF processing skill," which includes instructions for recognizing fields, handling layouts, and error checking, streamlining document processing tasks [3][11]. - Skills can be iteratively improved based on user feedback, allowing for the refinement of outputs to better meet specific requirements [7][8]. - The ability to store and recall user preferences within Skills reduces the need for repetitive input, enhancing efficiency in task execution [8][10]. Group 4: Future Implications - The future of Skills may significantly impact organizational competitiveness, as the ability to convert tacit knowledge into standardized modules could become a key differentiator [10][11]. - A mechanism called "Progressive Disclosure" is designed to optimize computational efficiency by loading only necessary information when required, thus minimizing resource consumption [10][11]. - While Skills democratize access to AI capabilities, there are concerns about potential risks associated with user-generated content, highlighting the importance of creating proprietary Skills for security [10][11].