[{"data":1,"prerenderedAt":355},["ShallowReactive",2],{"\u002Fcn\u002Fmemos_cloud\u002Ffeatures\u002Fadvanced\u002Fskill":3,"surround-\u002Fcn\u002Fmemos_cloud\u002Ffeatures\u002Fadvanced\u002Fskill":339},{"id":4,"title":5,"avatar":6,"banner":6,"body":7,"category":6,"desc":332,"description":173,"extension":333,"links":6,"meta":334,"navigation":6,"path":335,"seo":336,"stem":337,"__hash__":338},"docs\u002Fcn\u002Fmemos_cloud\u002Ffeatures\u002Fadvanced\u002Fskill.md","技能Skills",null,{"type":8,"value":9,"toc":316},"minimark",[10,15,27,34,70,73,77,84,87,131,133,137,140,142,150,153,164,174,176,183,186,192,194,201,204,215,221,246,248,255,258,269,272,283,289],[11,12,14],"h2",{"id":13},"_1-什么是memos技能skills","1. 什么是 MemOS 技能（Skills）？",[16,17,18,22,23,26],"p",{},[19,20,21],"strong",{},"技能（Skills）"," 是 Agent 在执行任务时可动态调用的",[19,24,25],{},"模块化能力包","。它由 Agent 根据对话上下文自动调度、按需注入，无需用户手动干预。这些技能通常由开发者协同编程大模型，基于开源项目或原生构思搭建，并在实际使用的过程中不断优化。",[16,28,29,30,33],{},"MemOS 主张“记忆即资产”。我们认为，那些在真实对话中沉淀下来的解决路径与用户偏好，本质上就是最宝贵的技能素材。基于此理念，MemOS ",[19,31,32],{},"现已支持从用户记忆中自动提炼技能","——将零散的交互历史固化为可复用、个性化的专业能力。",[35,36,37,42,51,54,57,64,67],"note",{},[16,38,39],{},[19,40,41],{},"MemOS 技能和已有的记忆有什么不同？",[43,44,45],"ul",{},[46,47,48],"li",{},[19,49,50],{},"静态事实 → 动态执行",[16,52,53],{},"记忆通常是静态的、事实性的，例如：“我住在上海”，“我喜欢简洁的回复”，这些信息为 Agent 推理提供必要上下文；",[16,55,56],{},"技能则是建立在记忆之上的可执行的行为能力，封装了一套明确的任务处理逻辑，例如「如何规划一套完整的出行方案」，指导 Agent 决策与行动。",[43,58,59],{},[46,60,61],{},[19,62,63],{},"碎片化 → 结构化",[16,65,66],{},"记忆通常是碎片化的，每条只描述一个事实或偏好；",[16,68,69],{},"技能则是高度结构化的，将多条相关记忆整合为一套完整任务方案，可在不同任务中复用。",[71,72],"br",{},[11,74,76],{"id":75},"_2-工作原理","2. 工作原理",[16,78,79],{},[80,81],"img",{"alt":82,"src":83},"image.png","https:\u002F\u002Fcdn.memtensor.com.cn\u002Fimg\u002F1769653199709_6ol3n7_compressed.png",[16,85,86],{},"上图展示了终端用户、您构建的 AI Agent 与 MemOS 的完整交互流程：",[88,89,90,98,122,128],"ol",{},[46,91,92,93,97],{},"调用 ",[94,95,96],"code",{},"add\u002Fmessage"," 接口将用户的对话消息传入 MemOS。",[46,99,100,101,103,104,107,108,110,111,114,115,117,118,121],{},"MemOS 接收到请求后，会依次完成以下处理，生成技能（Skill）文件：",[71,102],{},"a.  ",[19,105,106],{},"智能切片","：识别历史对话中的任务边界，切分成任务文本块；",[71,109],{},"b.  ",[19,112,113],{},"聚类提取","：将同类型的任务文本块聚类，结合用户的历史记忆，提取出结构化的技能文本。",[71,116],{},"c.  ",[19,119,120],{},"技能转化","：将技能转化为可运行、可被识别的技能（Skill）文件。",[46,123,92,124,127],{},[94,125,126],{},"search\u002Fmemory"," 接口检索记忆，MemOS 会统一返回与上下文相关的用户事实、偏好、工具记忆与匹配的技能（Skill）文件。",[46,129,130],{},"下载技能文件，将记忆和技能文件统一传给您自己部署的大模型，从而实现对长期经验与自动生成技能的有效利用。",[71,132],{},[11,134,136],{"id":135},"_3-使用示例","3. 使用示例",[16,138,139],{},"下面展示了 MemOS 基于历史对话，生成“旅行规划”技能的使用示例。",[71,141],{},[143,144,146,147],"h3",{"id":145},"_1-添加消息","1. ",[19,148,149],{},"添加消息",[16,151,152],{},"添加“高能量J人”与“旅行规划助手”的对话内容，“高能量J人”表达了对出行规划的几个要求：",[43,154,155,158,161],{},[46,156,157],{},"不喜欢回头路，特种兵",[46,159,160],{},"喜欢文化景点",[46,162,163],{},"需要提前确认天气和温度",[165,166,171],"pre",{"className":167,"code":169,"language":170},[168],"language-text","import os\nimport requests\nimport json\n\n# 替换成你的 API Key\nos.environ[\"MEMOS_API_KEY\"] = \"YOUR_API_KEY\"\nos.environ[\"MEMOS_BASE_URL\"] = \"https:\u002F\u002Fmemos.memtensor.cn\u002Fapi\u002Fopenmem\u002Fv1\"\n\ndata = {\n    \"user_id\": \"memos_user_123\",\n    \"conversation_id\": \"0127\",\n    \"messages\": [\n      {\"role\": \"user\", \"content\": \"下周我要去成都玩，帮我规划一个5天的出行计划，我喜欢不走回头路的特种兵出行，帮我标注路途中值得品尝的美食。\"},\n      {\"role\": \"assistant\", \"content\": \"...此处省略...\"},\n      {\"role\": \"user\", \"content\": \"我比较喜欢逛文化景点，商场什么的不太感兴趣。\"},\n      {\"role\": \"assistant\", \"content\": \"...此处省略...\"},\n      {\"role\": \"user\", \"content\": \"帮我在规划的时候，提前确认一下天气和温度，方便我准备行李。\"},\n      {\"role\": \"assistant\", \"content\": \"...此处省略...\"}\n    ]\n  }\nheaders = {\n  \"Content-Type\": \"application\u002Fjson\",\n  \"Authorization\": f\"Token {os.environ['MEMOS_API_KEY']}\"\n}\nurl = f\"{os.environ['MEMOS_BASE_URL']}\u002Fadd\u002Fmessage\"\n\nres = requests.post(url=url, headers=headers, data=json.dumps(data))\n\nprint(f\"result: {res.json()}\")\n\n","text",[94,172,169],{"__ignoreMap":173},"",[71,175],{},[143,177,179,180],{"id":178},"_2-检索记忆","2. ",[19,181,182],{},"检索记忆",[16,184,185],{},"假设该用户又一次向助手提出旅行规划的要求，传入用户的query，并开启召回skill：",[165,187,190],{"className":188,"code":189,"language":170},[168],"import os\nimport requests\nimport json\n\n# 替换成你的 API Key\nos.environ[\"MEMOS_API_KEY\"] = \"YOUR_API_KEY\"\nos.environ[\"MEMOS_BASE_URL\"] = \"https:\u002F\u002Fmemos.memtensor.cn\u002Fapi\u002Fopenmem\u002Fv1\"\ndata = {\n  \"query\": \"清明节我打算去云南，帮我规划7天的行程。\",\n  \"user_id\": \"memos_user_123\",\n  \"conversation_id\": \"0301\",\n  \"include_skill\": True # 开启召回skill\n}\nheaders = {\n  \"Content-Type\": \"application\u002Fjson\",\n  \"Authorization\": f\"Token {os.environ['MEMOS_API_KEY']}\"\n}\nurl = f\"{os.environ['MEMOS_BASE_URL']}\u002Fsearch\u002Fmemory\"\n\nres = requests.post(url=url, headers=headers, data=json.dumps(data))\n\nprint(f\"result: {res.json()}\")\n",[94,191,189],{"__ignoreMap":173},[71,193],{},[143,195,197,198],{"id":196},"_3-结果展示","3. ",[19,199,200],{},"结果展示",[16,202,203],{},"在以下的检索结果中，技能包含了：",[43,205,206,209,212],{},[46,207,208],{},"规划特种兵行程",[46,210,211],{},"推荐文化景点",[46,213,214],{},"关注了天气、温度，推荐需要携带的衣物。",[165,216,219],{"className":217,"code":218,"language":170},[168],"# 以下是 MemOS 生成的 Skill.md \n\n---\nname: 旅行行程规划\ndescription: 为旅行者设计多日行程，包括景点安排、交通方式和天气适配建议。\n---\n\n## Procedure\n1. 确定旅行者的兴趣和偏好 2. 收集目的地的景点和活动信息 3. 规划每日行程，确保动线高效且不走回头路 4. 添加当地特色美食推荐，确保体验丰富 5. 提供交通和住宿建议，兼顾便捷与舒适 6. 检查天气预报，调整行程和准备行李\n\n## Experience\n1. 高效动线设计减少通勤时间\n2. 景点优先，避免商业化场所\n3. 美食推荐增加体验丰富度\n4. 天气适配确保舒适出行\n\n## User Preferences\n- 不走回头路的行程安排\n- 文化景点优先，注重历史与文化体验\n- 根据天气调整行程和准备行李\n\n## Examples\n\n### Example 1\n\n# 旅行行程规划示例\n## Day 1\n- **行程**: 熊猫基地 → 东郊记忆 → 建设路美食街\n- **天气适配**: 阴天防风，适合逛文化街区\n- **美食推荐**: 军屯锅盔、豆浆\n- **交通**: 地铁+步行\n\n## Day 2\n- **行程**: 人民公园 → 成都博物馆 → 文殊院\n- **天气适配**: 小雨，室内博物馆为主\n- **美食推荐**: 钟水饺、陈麻婆豆腐\n- **交通**: 地铁+打车\n\n...\n\n## Additional Information\n\n### 行李准备指南\n根据目的地天气特点，采用洋葱式穿搭法，方便随时增减\n\n### 文化景点预约指南\n提供景点预约渠道、门票价格和开放时间\n\n",[94,220,218],{"__ignoreMap":173},[35,222,223,230],{},[16,224,225,228],{},[19,226,227],{},"技能的两种使用方法",[71,229],{},[43,231,232,239],{},[46,233,234,235,238],{},"如果你调用的模型 \u002F Agent 有使用 Skill 文件的能力，可以直接下载 ",[94,236,237],{},"skill_url"," 链接地址中的文件。",[46,240,241,242,245],{},"如果你调用的模型 \u002F Agent 没有使用 Skill 文件的能力，可以直接将 ",[94,243,244],{},"skill_value"," 转成字符串，添加到 prompt 中。",[71,247],{},[143,249,251,252],{"id":250},"_4-构建专属于你的技能","4. ",[19,253,254],{},"构建专属于你的技能",[16,256,257],{},"MemOS 基于不同用户的对话消息，能够创建专属于个人的技能。举例来说，我们另外构建了一个“低能量P人”与“旅行规划助手”的对话，当他提出：",[43,259,260,263,266],{},[46,261,262],{},"夜猫子，早上起不来",[46,264,265],{},"不想去太远、要赶路的景点",[46,267,268],{},"穿插小众景点，不走寻常路",[16,270,271],{},"MemOS构建的技能文件包含了：",[43,273,274,277,280],{},[46,275,276],{},"规划下午-晚上出行、不紧密的行程",[46,278,279],{},"推荐不太远、不需要赶路的路线",[46,281,282],{},"穿插小众景点。",[165,284,287],{"className":285,"code":286,"language":170},[168],"# 以下是 MemOS 生成的 Skill.md \n---\nname: 旅行行程规划\ndescription: 帮助用户规划旅行行程，确保舒适、高效地游览目的地\n\n---\n\n## Procedure\n\n1. 确定旅行目的和偏好 2. 收集目的地景点和活动信息 3. 根据用户偏好筛选景点 4. 安排每天的行程，包括交通和餐饮 5. 提供贴士和注意事项\n\n## Experience\n\n1. 避免长途奔波，选择交通便利的景点\n2. 合理安排每日行程，兼顾休闲和探索\n3. 充分利用夜间活动和景点，以提升旅行体验\n4. 挖掘小众景点，避开人潮，享受独特体验\n\n## User Preferences\n\n- 用户偏好晚起，避免长途旅行\n- 优先选择地铁直达的景点\n- 重视夜间活动和体验\n- 探索小众和非传统旅游路线\n\n## Examples\n\n### Example 1\n\n### Day 1: 国宝午后时光 + 小众老街夜游\n- **中午**: 自然醒 + 魁星楼街美食\n- **下午**: 成都大熊猫繁育研究基地\n- **晚上**: 柿子巷+桂花巷+泡桐树街夜游\n...\n\n### Example 2\n\n### Day 2: 三国文化 + 东门市井夜市\n- **中午**: 自然醒 + 武侯祠大街美食\n- **下午**: 武侯祠 + 红墙竹影\n- **晚上**: 东门市井+九眼桥酒吧街\n...\n",[94,288,286],{"__ignoreMap":173},[35,290,291,296],{},[16,292,293],{},[19,294,295],{},"现在就开始探索 MemOS 技能吧！ 🚀",[43,297,298,309],{},[46,299,300,301,308],{},"前往 ",[302,303,307],"a",{"href":304,"rel":305},"https:\u002F\u002Fmemos-dashboard.openmem.net\u002Fcn\u002Fskill\u002F",[306],"nofollow","控制台 - 技能页面","，查看基于用户历史对话自动生成的技能文件。",[46,310,311,312,315],{},"还没有技能？",[302,313,149],{"href":314},"\u002Fmemos_cloud\u002Fmem_operations\u002Fadd_message","即可触发生成。",{"title":173,"searchDepth":317,"depth":317,"links":318},2,[319,320,321],{"id":13,"depth":317,"text":14},{"id":75,"depth":317,"text":76},{"id":135,"depth":317,"text":136,"children":322},[323,326,328,330],{"id":145,"depth":324,"text":325},3,"1. 添加消息",{"id":178,"depth":324,"text":327},"2. 检索记忆",{"id":196,"depth":324,"text":329},"3. 结果展示",{"id":250,"depth":324,"text":331},"4. 构建专属于你的技能","添加用户对话消息，生成可被Agent复用的技能文件。","md",{},"\u002Fcn\u002Fmemos_cloud\u002Ffeatures\u002Fadvanced\u002Fskill",{"title":5,"description":173},"cn\u002Fmemos_cloud\u002Ffeatures\u002Fadvanced\u002Fskill","HzPF4OXZ79pYLoARZGuUWdbRqS8EoZ6AZzV_jvkJpd8",[340,348],{"title":341,"path":342,"stem":343,"icon":344,"framework":6,"module":6,"class":345,"target":-1,"active":346,"defaultOpen":346,"children":-1,"description":347},"自定义标签Tags","\u002Fcn\u002Fmemos_cloud\u002Ffeatures\u002Fbasic\u002Fcustom_tags","memos_cloud\u002Ffeatures\u002Fbasic\u002Fcustom_tags","i-ri-price-tag-3-line",[],false,"添加消息时按照你的业务需求使用标签。",{"title":349,"path":350,"stem":351,"icon":352,"framework":6,"module":6,"class":353,"target":-1,"active":346,"defaultOpen":346,"children":-1,"description":354},"知识库Knowledgebase","\u002Fcn\u002Fmemos_cloud\u002Ffeatures\u002Fadvanced\u002Fknowledge_base","memos_cloud\u002Ffeatures\u002Fadvanced\u002Fknowledge_base","i-ri-book-read-line",[],"创建项目关联的知识库，检索时结合记忆与知识库。",1774339748470]