Plugins 是可安装的软件包用于打包 agent 能力例如 skills并兼容 Claude agent plugin 规范。使用 plugin 可以一次性为 agent 安装一组相关能力。在目前的 9.4 发布中 Kibana 中开启agentBuilder:experimentalFeaturesadvanced setting 之前plugins library 会保持隐藏状态。开发 plugin我们来以之前的文章 “Elasticsearch智能搜索 - AI builderworkflow 及 skills” 为示例。我们看到创建所有的 skill 在一个界面里进行。它很不容易被管理。每次修改的时候需要进入到界面进行修改而且不知道是哪个版本。一种做法是把 skill 做成一个 plugin而 plugin 的构建可以放到仓库比如 github 中。这个 plugin 可以被很多开发者按照并进行使用。我开发的 propery-search plugin 在地址 https://github.com/liu-xiao-guo/real_estate_search_plugingit clone https://github.com/liu-xiao-guo/real_estate_search_plugin我们的 plugin 文件架构是这样的$ pwd /Users/liuxg/python/plugins $ tree -a -L 4 . ├── README.md ├── property-search │ ├── .claude-plugin │ │ └── plugin.json │ ├── README.md │ ├── scripts │ │ └── geocode_tool.py │ └── skills │ ├── .DS_Store │ └── search │ └── SKILL.md └── property-search-1.0.0.zip注其中的 两个 README.md 文件是一样的。外面的那个 README.md 只是为了在 github 上更好地展示。它不是 plugin property-search-1.0.0.zip 发布的一部分。注目前在 scripts 目录里含有一个 google_tool.py 的 python 代码但是 AI builder 并没有执行这个代码的沙箱。它仅只能提供参考给 LLM 使用。真正能帮我们做 DSL 模版搜索的是那个 SKILL.md 文件的书写。我们需要使用如下的命令来创建 plugincd property-search zip -r ../property-search-1.0.0.zip . -x *.DS_Store __pycache__/*生成的 property-search-1.0.0.zip 就是可安装的 plugin。实现步骤步骤一写入数据我们需要按照文章 “Elasticsearch智能搜索的 MCP” 写入文档到 Elasticsearch 中。步骤二创建 geocoding worflow 及相应的工具在我们的实现里我们需要根据位置信息来得到一个精确的经纬度以便实现相应的搜索。我们可以仿照之前的文章 “Elasticsearch创建 geocoding workflow并在 agent 中使用它进行位置搜索”。步骤三创建 agent我们创建一个如下的 Property search - plugin AgentAgent ID: property_search_pluginCustom InstructionsThis agent is used to search for properties: # Step 1: You are an information extraction assistant. Extract real estate search parameters from the user query. Parameter descriptions: - bathrooms: Number of bathrooms - bedrooms: Number of bedrooms - tax: Real estate tax amount - maintenance: Maintenance fee amount - square_footage_min: Minimum property square footage. If only a max square footage is provided, set this to 0. Otherwise set this to the minimum square footage specified by the user. - square_footage_max: Maximum property square footage - home_price_min: Minimum home price. If only a max home price is provided, set this to 0. Otherwise set this to the minimum home price specified by the user. - home_price_max: Maximum home price - features: Home features such as AC, pool, updated kitchens, etc should be listed as a single string. - location: City, state, or full address if present. Rules: - Only include parameters explicitly mentioned. - property_features must be a single space-separated string. - Return ONLY a JSON object (not a string, no quotes, no extra text, no explanations). - Do not include explanations. Example JSON: { query: Find a home within 10 miles of Miami, Florida that has 2 bedrooms, 2 bathrooms, central air, and tile floors, with a budget up to $300,000. bathrooms: 2, bedrooms: 2, home_price_min: 0, home_price_max: 300000, property_features: central air tile floors, location: Miami, Florida } # Step 2: - Use the above constructed JSON format, and do a DSL template search. If you need to convert it to ES|QL queries, please do follow exactly the DSL template search ranges. - Before you do the searches, please DO refer to the requirements specified by the property-search plugin. - Please print out the search template used for search, and then print out the top **4 results** for viewing.VisibilityPublicDisplay name: Property search - pluginDisplay description: Property search - plugin选择 get_coordinate_by_location 工具安装 plugin我们按照如下的步骤来安装 plugin在 agent 中选择这个 plugin一旦 plugin 被安装那么它就像是一个库一样可以被许多的 agents 使用。我们来选择这个 property-search 的 plugin测试我们使用如下的例子来进行测试Find a home within 10 miles of Miami, Florida that has 2 bedrooms, 2 bathrooms, central air, and tile floors, with a budget up to $300,000.从上面我们可以看出来我们得到了我们想要的搜索结果。最后祝大家学习愉快