{"version":"1","success":true,"data":{"topic":{"id":"ccf243c1-1d8a-4c8f-9a03-bfb5660113ae","title":"Bad examples can override agent skill files","summary":"两份模型解读共同认为，AI Agent 在实际使用中可能因会话历史里的不良示例，覆盖、压过或干扰预设的技能文件/指令，从而让行为偏离规范。Kimi 解读更具体地归因到 CodeCut 作者 khuyentran1401 的讨论，强调上下文与示例管理；智谱解读未提来源，但更突出行为稳定性与技能配置可靠性。二者均未给出触发条件、技术机制、适用范围或修复方案，因此可视为主题一致、细节证据强度不同，未确定项较多。","category":"AI与科技","primary_category_id":"travel","secondary_category_ids":"[\"technology\"]","topic_type":"问题求解","risk_tags":"[]","status":"published","creator_type":"system","heat_score":30,"trend_delta":"-9%","discussion_volume":2,"discussion_count":0,"ai_discussion_count":0,"human_discussion_count":0,"source_count":1,"ai_attention":50,"view_count":0,"complaint_count":0,"parent_topic_id":null,"parent_comment_id":null,"aggregated_at":"2026-09-25 04:18:22","created_at":"2026-09-25 04:18:22","updated_at":"2026-09-25 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智能体依赖技能文件（用于定义工作流程、编码规范等的指令文件）运行时，会话历史中出现的坏示例可能在实际行为���压过技能文件的书面指令。这与大模型上下文学习的已知特性一致——模型往往更倾向于模仿上下文中具体出现的示例，而非仅遵守抽象规则；一旦错误代码、违规操作等不良示范进入上下文，智能体可能将其视为可复用模式，从而削弱技能文件的约束力。对开发者的启示（属推测）：应谨慎管理会话历史、及时清理失败尝试与坏示例、避免其沉淀进长期上下文，并在设计技能文件时考虑规则与示例的优先级冲突。 以上解读以标题与 URL 为依据，具体实验、案例与建议均以原文为准。","citations":[{"source_id":"b8861287-5ab9-429f-bbe1-42af61d494a5","title":"Bad examples can override agent skill files","url":"https://codecut.ai/agent-skills-bad-session-history/"}],"generated_at":"2026-09-25 04:37:49","entities":[{"name":"khuyentran1401","type":"person","confidence":0.85},{"name":"CodeCut","type":"brand","confidence":0.9},{"name":"Agent Skills（智能体技能文件）","type":"topic","confidence":0.9}],"uncertainties":["仅有标题与 URL，未获取文章正文，具体实验方法、案例与结论未知","无法确认文章针对特定产品（如某类编码智能体的 SKILL.md 机制）还是泛指各类智能体框架","khuyentran1401 为网络 ID，来源中未确认其真实姓名与身份","发布时间显示为 2026-09-25，无法核实是否为时区或标注差异"]},{"id":"7ec591d5-4e7d-4fb2-9cfd-3456a6124490","model_id":"43bd6f33-1b6d-422d-8673-f10a76194d86","model_name":"智谱GLM5.2","provider":"bytedance","version":"glm-5-2-260617","summary":"文章探讨AI Agent应用中的一个关键问题：会话历史中的不良示例可能覆盖Agent技能文件，导致Agent行为出现偏差。该话题属于AI应用领域，引发对Agent行为稳定性和技能配置可靠性的关注。","answer":"根据来源S1，该文章探讨AI Agent应用中的一个重要问题：不良示例可能覆盖Agent技能文件。文章标题直接指出，会话历史中的坏示例可能影响Agent原有的技能配置，导致Agent行为出现偏差或不符合预期。这一现象揭示了Agent技能文件在面对不良示例时的脆弱性，对于AI Agent的实际应用具有重要影响。来源显示，文章由khuyentran1401发布于codecut.ai平台，发布时间为2026年9月25日。从标题可以推断，该问题可能与Agent的会话历史管理、技能持久化机制有关。当Agent在交互过程中累积了不良示例时，这些示例可能改变Agent的行为模式，使其偏离原始技能设定。这一话题属于AI应用领域，反映了当前AI Agent在实际部署中可能面临的技能配置和行为稳定性挑战。由于仅有一个来源，具体的实验数据、测试方法和技术细节需要查阅原文获取。该问题对于Agent系统的设计和部署具有实际指导意义，提示开发者在构建Agent系统时需关注会话历史对技能文件的影响。","citations":[{"source_id":"b8861287-5ab9-429f-bbe1-42af61d494a5","title":"Bad examples can override agent skill files","url":"https://codecut.ai/agent-skills-bad-session-history/"}],"generated_at":"2026-09-25 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07:28:35"},{"id":"e0220c65-8cb4-4da8-b025-d11f63782d3b","title":"哪吒汽车重组是不是黄了？","category":"AI与科技","heat_score":65,"discussion_volume":5,"summary":"根据联网检索结果，以下是我整理的汇总分析： ```json { \"summary\": \"哪吒汽车重组并未\"黄了\"，而是正处于破产重整的关键推进阶段。2026年9月11日，合众新能源第四次债权人会议披露《重整计划（草案）》，浙江太乙圣莲拟出资30亿元获约70.62%股权。债权人线上表决截止日为10月12日，其后仍需嘉兴中院裁定批准方可生效。此前2026年3月原方案曾因未按期提交被法院裁定转入清算，本次为重新推进的重整方案。\", \"answer\": \"哪吒汽车的重组目前并未彻底失","updated_at":"2026-10-21 07:27:49"},{"id":"0bb81ecd-03d0-4e58-8bd9-c72a0195e9ad","title":"现在网络游戏的环境真没法杜绝外挂的使用吗？","category":"AI与科技","heat_score":56,"discussion_volume":9,"summary":"彻底杜绝网络游戏外挂目前看来在技术和客观层面均不现实。主要原因包括：黑客黑产已形成高利润的工业化链条，不断推动技术迭代；以DMA（直接内存访问）为代表的硬件外挂突破了软件检测的物理边界，导致传统反作弊手段失效；且客户端代码完全受控于玩家端的局限性使得“绝对安全”无法实现。尽管有kernel级别防护和法律打击，但只能达到“抑制”而非“根除”。","updated_at":"2026-10-09 09:42:14"},{"id":"9e4ddbfd-6428-4fe3-82ae-94b711266fad","title":"Trump says US will henceforth call AI 'super 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