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      "name": "环境准备与初始化",
      "description": "deployment-environment-setup",
      "prompt": "创建部署前的环境准备与初始化指南。说明 PostgreSQL + pgvector、Redis、Elasticsearch、Neo4j、DuckDB 等外部依赖的安装要求、端口和版本兼容性，并给出最小可用环境的安装命令示例。详细说明 deploy/env.sh 中关键变量的含义与生产修改项：数据库连接、Redis、本地文件存储路径 STORAGE_LOCAL_ROOT_PATH/STORAGE_LOCAL_BASE_URL、Agent RAG、DuckDB 资源预算、向量模型路径 ZSJZ_EMBEDDING_MODEL_PATH、AI 清洗向量索引、聊天附件解析、登录安全窗口等。补充 SQL 初始化步骤：gateway_service/gateway_node 表、业务主库表结构、pgvector 扩展启用。说明 Spring Profile 切换方式（SPRING_PROFILES_ACTIVE）以及 dev/pro 配置差异。包含常见环境问题排查：端口冲突、pgvector 未启用、Redis 不可用导致登录异常、ES/Neo4j 可选依赖缺失时的降级行为。",
      "progress_status": "completed",
      "dependent_files": "deploy/env.sh,sql/gateway.sql,sql/create_table_2.sql,ai-server/pom.xml,ai-server/src/main/resources/application-dev.yaml,ai-server/src/main/resources/application-pro.yaml",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "67aa6a8d-c25c-435e-be2c-9a5fda6668b7",
      "layer_level": 1,
      "kk_dependent_files": [
        "deploy/env.sh",
        "sql/gateway.sql",
        "sql/create_table_2.sql",
        "ai-server/pom.xml",
        "ai-server/src/main/resources/application-dev.yaml",
        "ai-server/src/main/resources/application-pro.yaml"
      ]
    },
    {
      "id": "dfcc2c4e-4392-42f2-9bab-4f652761f880",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "网关路由表结构",
      "description": "gateway-schema",
      "prompt": "创建网关数据库设计文档，重点说明 gateway_service、gateway_node、gateway_user_route（或实际使用的服务注册与用户绑定表）的表结构。详细描述每个字段的数据类型、主键、外键、索引和业务含义，包括服务标识、节点地址、健康状态、用户名与 ai-server 节点的绑定关系。结合 StickyRouteFilter 和 LoginResponseFilter 的逻辑，解释这些表如何支撑粘性路由、登录绑定、503 异常处理和服务/节点管理接口。补充建表 SQL 示例、关键字段约束、查询性能建议，以及多节点部署下的数据一致性注意事项。",
      "progress_status": "completed",
      "dependent_files": "sql/gateway.sql",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "c1789760-0a39-4847-879e-bd14a1ed7b37",
      "layer_level": 1,
      "kk_dependent_files": [
        "sql/gateway.sql"
      ]
    },
    {
      "id": "e6253e7f-3ead-4cd2-84c5-bd9c93288a0e",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "Electron 主进程与生命周期",
      "description": "electron-main-process",
      "prompt": "为 Electron 主进程与生命周期编写详细文档。说明 ai-electron/electron/main.ts 如何通过 ee-core.ElectronEgg 创建应用、注册 ready / electron-app-ready / window-ready / before-close 等生命周期钩子，并调用 app.run() 启动。解释 preload/lifecycle.ts 中各生命周期钩子的执行顺序和职责边界，以及 preload/index.ts 的 preload() 函数如何在预加载阶段创建托盘服务（trayService）和安全服务（securityService）。说明主进程与渲染进程的职责划分：主进程负责窗口、系统能力、安全初始化；渲染进程只负责 UI 和业务逻辑。给出新增生命周期钩子、自定义 preload 初始化的步骤示例，并包含常见问题排查：主进程未启动、生命周期钩子未执行、preload 加载失败、托盘或安全服务异常等。",
      "progress_status": "completed",
      "dependent_files": "ai-electron/electron/main.ts,ai-electron/electron/preload/lifecycle.ts,ai-electron/electron/preload/index.ts,ai-electron/package.json",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "d36adb59-0865-4057-ac6b-1a3762816c01",
      "layer_level": 1,
      "kk_dependent_files": [
        "ai-electron/electron/main.ts",
        "ai-electron/electron/preload/lifecycle.ts",
        "ai-electron/electron/preload/index.ts",
        "ai-electron/package.json"
      ]
    },
    {
      "id": "f5ed2513-391a-4b75-8007-bb3d5216e4df",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "清洗模板与字段映射",
      "description": "ai-clean-templates",
      "prompt": "编写 AI 数据清洗中清洗模板与字段映射的详细文档。说明 AiCleanTemplate、AiCleanField、RuleBind、AiRulePlan 等实体的字段定义、主外键关系和业务含义，解释清洗模板如何描述目标表结构、字段短名、规则计划以及字段到目标列的映射关系。详细说明模板加载流程：从数据库读取模板、构建 TemplateCandidate、由 AiTemplateMatcher 结合表头指纹和 HeaderNormalizer 进行匹配。给出创建模板、绑定规则、定义字段短名和字段映射的完整示例，包括 CSV 表头、Excel 列名与目标字段的对应关系。说明字段短名（field short names）在智能匹配中的作用，以及与 Synonym 的区别。补充常见问题：模板未命中、字段映射错位、短名冲突、规则计划类型不匹配等，并给出排查建议。",
      "progress_status": "completed",
      "dependent_files": "sql/ai_clean.sql,sql/ai_clean_field_short_names.sql,ai-server/src/main/java/com/zsjz/ai/module/aiclean/entity/AiCleanTemplate.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/entity/AiCleanField.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/model/RuleBind.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/rule/AiRulePlan.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/match/AiTemplateMatcher.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/match/TemplateCandidateLoader.java",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "fbd0f840-7bf0-40b1-9ae4-01dd991a8752",
      "layer_level": 1,
      "kk_dependent_files": [
        "sql/ai_clean.sql",
        "sql/ai_clean_field_short_names.sql",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/entity/AiCleanTemplate.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/entity/AiCleanField.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/model/RuleBind.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/rule/AiRulePlan.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/match/AiTemplateMatcher.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/match/TemplateCandidateLoader.java"
      ]
    },
    {
      "id": "114b42fc-097d-4ff9-b78a-b1f128492359",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "快速开始",
      "description": "getting-started",
      "prompt": "编写清鉴 AI 调查工具的快速开始指南，覆盖开发机环境准备、依赖安装、服务启动顺序和首次运行步骤。说明需要 Java 25、Maven、Node.js、pnpm/npm、PostgreSQL、pgvector、Redis、DuckDB 等前置条件；描述如何初始化 sql/*.sql 脚本，启动 ai-gateway 和 ai-server，再通过 pnpm dev 或构建命令启动 Electron 客户端。说明首次运行时输入服务端地址、登录绑定、激活/授权单元和水印的基本流程。包含常见启动失败排查项，如端口冲突、数据库连接、向量扩展未启用、regInfo.exe 权限问题等。内容应简洁明了，适合第一次接触项目的开发者在 10–20 分钟内跑通本地环境。",
      "progress_status": "completed",
      "dependent_files": "readme.md,deploy/env.sh,cmd/uninstall.bat,cmd/uninstall.sh,ai-electron/package.json,ai-electron/frontend/package.json,ai-server/pom.xml,ai-gateway/pom.xml",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "order": 1,
      "kk_dependent_files": [
        "readme.md",
        "deploy/env.sh",
        "cmd/uninstall.bat",
        "cmd/uninstall.sh",
        "ai-electron/package.json",
        "ai-electron/frontend/package.json",
        "ai-server/pom.xml",
        "ai-gateway/pom.xml"
      ]
    },
    {
      "id": "1acb4aac-20b1-4e60-9d3a-4d49412f11ef",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "文档上传、解析与索引生命周期",
      "description": "knowledge-doc-lifecycle",
      "prompt": "创建文档上传、解析、向量化、存储和重试生命周期的详细文档。说明 KnowledgeDocService.upload 如何处理 multipart 文件、调用 KnowledgeDocParser 提取文本、通过事件或异步任务触发 KnowledgeDocIndexer 进行向量化并写入 pgvector；解释 reindex 重试机制、仅上传者权限校验、下载时写 KnowledgeDocDownloadLog 的流程。文档应包含上传、删除、重试、下载的 REST API 接口定义，包括请求参数、响应结构、错误码和 x-token 鉴权要求。补充支持的文档格式、文件大小限制、大文档分块策略、索引失败状态、去重逻辑、文件存储路径、性能优化建议和常见异常处理方案。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/knowledge/controller/KnowledgeBaseController.java,ai-server/src/main/java/com/zsjz/ai/module/knowledge/service/KnowledgeDocService.java,ai-server/src/main/java/com/zsjz/ai/module/knowledge/KnowledgeDocParser.java,ai-server/src/main/java/com/zsjz/ai/module/knowledge/KnowledgeDocIndexer.java,ai-server/src/main/java/com/zsjz/ai/module/knowledge/event/KnowledgeDocIndexEvent.java,ai-server/src/main/java/com/zsjz/ai/module/knowledge/entity/KnowledgeDoc.java,ai-server/src/main/java/com/zsjz/ai/module/knowledge/entity/KnowledgeDocDownloadLog.java,ai-server/src/main/java/com/zsjz/ai/module/knowledge/vo/KnowledgeDocVO.java,ai-electron/frontend/src/ai/components/KnowledgeDocModal.ts",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "fde671b0-e5b4-4ff9-9baa-df07ebc75177",
      "layer_level": 1,
      "order": 1,
      "kk_dependent_files": [
        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/controller/KnowledgeBaseController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/service/KnowledgeDocService.java",
        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/KnowledgeDocParser.java",
        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/KnowledgeDocIndexer.java",
        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/event/KnowledgeDocIndexEvent.java",
        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/entity/KnowledgeDoc.java",
        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/entity/KnowledgeDocDownloadLog.java",
        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/vo/KnowledgeDocVO.java",
        "ai-electron/frontend/src/ai/components/KnowledgeDocModal.ts"
      ]
    },
    {
      "id": "21342d52-98e3-4654-9724-072359e1c6f2",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "后端服务部署",
      "description": "deployment-backend-services",
      "prompt": "创建 ai-gateway 与 ai-server 的生产部署指南。说明 Maven 父工程编译顺序、打包产物和启动命令；分别描述 GatewayApplication 网关服务和 ai-server 业务服务的启动流程、依赖加载顺序、健康检查行为和日志位置。解释环境变量导入方式：`set -a; source deploy/env.sh; set +a` 与 systemd EnvironmentFile 两种用法，并强调数据库口令权限控制。说明 ai-gateway 的粘性路由职责：服务注册、节点选择、CORS、登录绑定转发，以及 ai-server 的模块化启动（plat、agent、aiclean、knowledge、graph、person、call、trans、track、govern、search、dm、otg、external）。给出典型部署拓扑：单节点开发环境、多节点 ai-server + 单网关、多网关高可用场景。补充性能参数调优建议：Spring 调度池、HTTP codecs、multipart 大小、DuckDB 内存比例、线程数、RAG top_k 等，并结合 deploy/env.sh 给出生产推荐值。包含故障排查：Gateway 503、跨域失败、登录态丢失、Redis 断开、ES/Neo4j 连接超时、文件上传超限等。",
      "progress_status": "completed",
      "dependent_files": "deploy/env.sh,ai-gateway/src/main/java/com/zsjz/gateway/GatewayApplication.java,ai-gateway/pom.xml,ai-server/pom.xml,pom.xml",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "67aa6a8d-c25c-435e-be2c-9a5fda6668b7",
      "layer_level": 1,
      "order": 1,
      "kk_dependent_files": [
        "deploy/env.sh",
        "ai-gateway/src/main/java/com/zsjz/gateway/GatewayApplication.java",
        "ai-gateway/pom.xml",
        "ai-server/pom.xml",
        "pom.xml"
      ]
    },
    {
      "id": "22ed1e10-d4ca-42c7-801c-8bda48b58052",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "登录请求与响应过滤链",
      "description": "login-binding-filters",
      "prompt": "创建登录相关过滤链的详细文档，说明 LoginRequestFilter 和 LoginResponseFilter 如何配合 StickyRouteFilter 完成用户与服务节点的绑定。解释 LoginRequestFilter 如何识别登录请求并将 username 写入 GatewayAttributes.LOGIN_USERNAME 与 LOGIN_REQUEST，使 StickyRouteFilter 能进入 decideForLogin 分支。说明 LoginResponseFilter 如何在登录成功后根据 LOGIN_CHOSEN_NODE_ID 把用户绑定到具体 ai-server 节点，并持久化到数据库。对比登录前后 token 解析结果的变化，解释“登录时不立即写库、由响应过滤器落库”的原因。给出典型登录流程时序图，包括客户端、Gateway、ai-server、PostgreSQL 之间的交互。补充用户名冲突、重复登录、强制踢下线等边界情况的处理。",
      "progress_status": "completed",
      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginRequestFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginResponseFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/route/GatewayAttributes.java",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "198e92ee-5762-48f9-835d-17889a315be1",
      "layer_level": 1,
      "order": 1,
      "kk_dependent_files": [
        "ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginRequestFilter.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginResponseFilter.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/route/GatewayAttributes.java"
      ]
    },
    {
      "id": "30a9faef-23f4-406d-8889-3da2c96ba102",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "LLM Provider 管理与模型工厂",
      "description": "agent-model-provider",
      "prompt": "为 LLM Provider 管理与模型工厂创建详细文档。说明 pom.xml 中 agentscope-harness、agentscope-extensions-model-dashscope、ollama、openai、mem0、redis 等依赖的作用；解释 AgentEntity、AgentModelService、AgentModelFactory 如何注册和管理 DashScope/Ollama/OpenAI 三种 Provider。描述模型配置项（如 base_url、api_key、model_name）、模型枚举、可用性与健康检查策略。给出示例：新增一个 LLM Provider、切换默认模型、通过 AgentModelController 查询模型列表和状态。补充问题排查：DashScope Key 无效、Ollama 服务不可达、OpenAI 代理超时、模型枚举不生效等。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,ai-server/src/main/java/com/zsjz/ai/module/agent/entity/AgentEntity.java,ai-server/src/main/java/com/zsjz/ai/module/agent/service/AgentModelFactory.java,ai-server/src/main/java/com/zsjz/ai/module/agent/service/AgentModelService.java,ai-server/src/main/java/com/zsjz/ai/module/agent/service/impl/AgentModelServiceImpl.java,ai-server/src/main/java/com/zsjz/ai/module/agent/converter/AgentModelConverter.java,ai-server/src/main/java/com/zsjz/ai/module/agent/converter/AgentModelProviderConverter.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentModelController.java",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "ec9a24fa-b5b6-4b28-96ab-06ee3089519f",
      "layer_level": 1,
      "order": 1,
      "kk_dependent_files": [
        "ai-server/pom.xml",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/entity/AgentEntity.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/service/AgentModelFactory.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/service/AgentModelService.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/service/impl/AgentModelServiceImpl.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/converter/AgentModelConverter.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/converter/AgentModelProviderConverter.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentModelController.java"
      ]
    },
    {
      "id": "41e369d2-9662-4e1b-b62f-21de646b34c9",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "Gateway Token 一致性与登录绑定",
      "description": "gateway-token-consistency",
      "prompt": "编写 Gateway 层 token 一致性、登录绑定与粘性路由交互的详细文档。说明 LoginRequestFilter 如何从请求中提取 username/token，StickyRouteFilter 如何根据 userId 选择 ai-server 节点并重写目标 URL，LoginResponseFilter 如何在登录成功后将用户名与服务节点绑定写入数据库。解释为什么 token 必须在客户端、Gateway、ai-server 之间保持一致，以及节点 DOWN 时返回 503 不自动切换的原因。给出登录流程时序图、常见失败场景（未绑定节点、token 过期、节点不可用）及排查步骤。",
      "progress_status": "completed",
      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/route/StickyRouteFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginRequestFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginResponseFilter.java",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "c77f0da0-55bc-4f69-9e32-f4aca699b57c",
      "layer_level": 1,
      "order": 1,
      "kk_dependent_files": [
        "ai-gateway/src/main/java/com/zsjz/gateway/route/StickyRouteFilter.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginRequestFilter.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginResponseFilter.java"
      ]
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    {
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      "name": "桌面客户端架构",
      "description": "desktop-client-architecture",
      "prompt": "创建 Electron 桌面客户端架构文档。重点解释主进程与渲染进程的职责分离：main.ts 基于 ee-core.ElectronEgg 注册生命周期钩子和 preload，preload 桥接暴露 Node/Electron API 给渲染进程，App.vue 初始化主题、国际化、水印和授权单元。说明前端工程结构（Vite + Vue 3 + Ant Design Vue + TypeScript），如何动态绑定 ai-server 地址、加载离线地图 china.pmtiles、调用 SSE Agent 对话、管理本地缓存与服务端地址。补充 IPC 安全模型、构建打包脚本、自动更新配置和常见问题排查。提供从启动到登录、发起 Agent 请求的最小代码路径示例。",
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      "description": "build-and-scripts",
      "prompt": "创建构建命令与脚本参考文档。说明 Maven 父工程与 ai-server、ai-gateway 子模块的构建命令；pnpm dev、build、start 等前端开发命令；Electron 打包命令和 electron-builder 输出产物；安装、启动、卸载脚本的作用和使用方式。解释 deploy/env.sh 环境变量脚本如何覆盖后端配置，以及 Linux/macOS 下执行权限要求。给出典型工作流：拉取代码、安装依赖、启动 Gateway 和 ai-server、启动 Electron 客户端、打包 Windows/macOS/Linux 安装包。列出常见错误如端口冲突、依赖缺失、打包失败和解决方法。",
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        "ai-electron/frontend/bin/install.sh",
        "ai-electron/frontend/bin/install.bat",
        "ai-electron/frontend/bin/build.sh",
        "ai-electron/frontend/bin/build.bat",
        "ai-electron/frontend/bin/startup.sh",
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        "cmd/uninstall.bat",
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      "description": "plat-user-schema",
      "prompt": "创建平台基础与用户授权相关表的数据库设计文档。说明 plat 模块中的系统配置、表信息、授权单元、会话、缓存、日历等表，以及 user 表的用户信息、账号状态、设备或机器码相关信息。详细列出主键、外键、唯一约束、索引和关键字段语义；解释 Sa-Token 会话、客户端 token、许可证校验、水印与授权单元之间的关系。给出典型查询场景，例如按用户查会话、查绑定 ai-server 节点、查授权有效期。补充数据安全要求、敏感字段保护、备份恢复建议和常见运维问题排查方法。",
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      "prompt": "编写 AI 数据清洗中同义词管理功能的详细文档。说明 AiCleanSynonym 实体结构、字段含义、数据来源及初始化脚本 ai_clean_synonym_init.sql 的作用。解释同义词与清洗模板字段短名的区别：同义词用于增强表头识别和语义匹配，字段短名用于模板侧的标准命名。详细描述增删改查接口（AiCleanSynonymController）和服务层逻辑（AiCleanSynonymService），包括同义词分组、别名、标准字段之间的关系。给出添加同义词、批量导入、查询生效范围的实际示例。说明同义词如何被 AiTemplateMatcher 或表头匹配链路使用，以及在多用户/多案件场景下的隔离策略。补充常见问题：新增同义词未生效、别名冲突、初始化脚本重复执行、同义词未参与匹配等。",
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      "name": "模块化架构与统一分层",
      "description": "module-architecture",
      "prompt": "编写 ai-server 模块化架构文档，聚焦 module/* 下的业务域划分和统一分层模式。说明每个模块通常包含 controller、service、mapper/entity 的职责边界，以及跨模块调用应通过 Service 接口而非直接依赖实现。解释模块间耦合原则：避免循环依赖、通过领域事件或共享 DTO 传递数据、网关只感知 ai-server 整体而不感知内部模块。给出新增业务模块的标准步骤：创建 module、定义 entity、Mapper、Service、Controller，注册路由，并维护对应 SQL 脚本。补充代码风格、命名约定和可测试性建议。",
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      "name": "认证与系统基础接口",
      "description": "auth-and-system-api",
      "prompt": "创建认证与系统基础接口的 API 文档，覆盖 /auth、/user、/sys、/case、/tpl、/tower 等 plat 模块控制器。重点说明登录流程：前端如何调用认证接口获取 token，x-token 如何随后续请求携带，Sa-Token 如何与 Gateway 粘性路由配合完成用户绑定。记录用户信息、授权单元、系统信息、案件数据源、表模板、塔台相关接口的 HTTP 方法、URL、请求参数、响应字段、分页格式和错误码。说明登录失效、账号被顶下线、强制登录后清理缓存的行为对前端的影响。提供 curl 和前端调用示例，并给出 401、403、503 等错误的排查步骤。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/plat/controller/AuthController.java,ai-server/src/main/java/com/zsjz/ai/module/plat/controller/UserController.java,ai-server/src/main/java/com/zsjz/ai/module/plat/controller/SystemController.java,ai-server/src/main/java/com/zsjz/ai/module/plat/controller/CaseInfoController.java,ai-server/src/main/java/com/zsjz/ai/module/plat/controller/TableInfoController.java,ai-server/src/main/java/com/zsjz/ai/module/plat/controller/TowerController.java",
      "gmt_create": "2026-10-28T07:55:29Z",
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        "ai-server/src/main/java/com/zsjz/ai/module/plat/controller/SystemController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/plat/controller/CaseInfoController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/plat/controller/TableInfoController.java",
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      "name": "通话模块 call",
      "description": "business-call",
      "prompt": "为通话模块 call 创建详细文档。说明该模块负责通话记录、夜间通话、连续通话、敏感通话、开放信息等调查相关实体的存储与查询。解释通话记录与人员 person 的关系（主叫/被叫），以及与交易、轨迹、治理树之间的交叉分析价值。梳理通话实体字段、时间范围过滤、号码匹配、去重规则、分页和聚合统计方式。给出常用查询示例：查找某人的所有通话、夜间通话分析、连续通话识别、敏感通话预警、通话双方关系图。说明数据量较大时的索引优化、分区策略和查询性能注意事项。",
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      "name": "Preload 桥接与安全模型",
      "description": "electron-preload-bridge",
      "prompt": "为 Electron preload 桥接与安全模型编写详细文档。解释启用 contextIsolation 后渲染进程无法直接使用 Electron API，因此通过 bridge.ts 中的 contextBridge.exposeInMainWorld('electron', {...}) 暴露受控接口，当前仅暴露 ipcRenderer。说明 preload/index.ts 的 preload() 函数在渲染进程上下文之前运行，用于创建 trayService 和 securityService，避免将 Node/Electron 能力直接泄露给渲染进程。文档应覆盖 IPC 通道设计原则、最小权限暴露策略、跨进程通信的安全边界，以及为什么不应把 BrowserWindow、fs、child_process 等危险 API 暴露到 window.electron。给出新增安全 IPC 接口的示例，包括主进程 service、preload 桥注册、前端调用方式。包含常见问题：contextBridge 报错、window.electron 为 undefined、IPC 事件无响应、权限不足等。",
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      "description": "agent-rag-schema-vector",
      "prompt": "为 RAG Schema、向量检索与知识库集成创建详细文档。结合 agentscope-extensions-rag-simple、pgvector 和 Spring AI Tika，说明 Schema Catalog 如何描述业务表结构，RAG 如何在 Agent 对话时根据意图对问题进行向量检索，并将上下文注入提示词。解释 RagIndexStatus 表示的索引状态，以及知识库下载日志、嵌入调试接口与 RAG 的关系。给出示例：开启 RAG 后发送调查类问题、查看命中片段、重新构建向量索引。补充常见问题：pgvector 未初始化、向量索引为空、相似检索召回率低、Schema 字段名不一致等。",
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      "name": "Agent 对话与 RAG 接口",
      "description": "agent-chat-and-rag-api",
      "prompt": "创建 Agent 对话与 RAG 接口的 API 文档，覆盖 /chat、/models、/agents、/tool-packs、/capability、/agent/artifact、/py/files 以及 Insight 相关控制器。重点说明 Agent 对话 SSE 接口：连接建立方式、请求头中的 x-token、消息体格式、SSE 事件类型、增量内容字段、结束事件、心跳保活机制和中断重连策略。同时文档化模型列表、专家目录、工具包、能力枚举、Artifacts 和 Python 文件管理等 REST 接口，包括 URL、HTTP 方法、请求参数、响应体结构和错误码。说明 AgentScope、LLM Provider、RAG Schema、向量检索与 Python 执行器在对话流程中的作用。提供 curl 和前端 fetch/SSE 示例，并给出 LLM 不可用、RAG 无结果、SSE 断流、Token 过期等问题的排查方法。",
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      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentChatController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentModelController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentExpertController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentToolPackController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentCapabilityController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentArtifactController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentPythonFileController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/insight/controller/InsightController.java",
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        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentExpertController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentToolPackController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentCapabilityController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentArtifactController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentPythonFileController.java",
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      "name": "Agent、专家、工具与聊天附件表",
      "description": "agent-schemas",
      "prompt": "创建 Agent 相关数据库设计文档，涵盖 agent_expert、agent_tool、chat_attachment、insight_agent_tables 等表。说明 Agent 专家目录、工具定义、聊天附件存储、Insight 数据模型之间的关联关系。详细描述每条表的主键、外键、JSON/文本字段、文件路径或二进制引用字段、状态字段及业务规则。解释这些表如何支撑 Agent 对话、RAG Schema、Workspace Catalog、Artifact、Python 执行器和 Insight 功能。提供 ER 关系图、典型插入/查询示例，并说明大附件、向量检索元数据和会话数据的生命周期管理与清理策略。",
      "progress_status": "completed",
      "dependent_files": "sql/agent_expert.sql,sql/agent_tool.sql,sql/chat_attachment.sql,sql/insight_agent_tables.sql",
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        "sql/insight_agent_tables.sql"
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      "name": "regInfo.exe 许可证校验流程",
      "description": "reginfo-license-validation",
      "prompt": "编写 regInfo.exe 许可证校验流程的详细文档。说明客户端如何调用或集成 regInfo.exe，如何获取机器码、过期时间、单位信息，以及如何将这些信息与授权单元进行比对。解释许可证有效、即将过期、已过期等不同状态下的系统行为；说明授权单元在 `/sys/info` 或相关接口返回后的展示位置、水印渲染机制。提供 regInfo.exe 命令行用法、参数说明、返回值约定、错误码含义，以及许可证失效时的回退策略和用户提示。包含部署时安装 regInfo.exe、首次激活、更新许可证的操作示例。",
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      "dependent_files": "readme.md,ai-electron/package.json,ai-electron/frontend/package.json",
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "交易模块 trans",
      "description": "business-trans",
      "prompt": "为交易模块 trans 创建详细文档。说明该模块覆盖资金流水、固定存款、现金、大额、频率、敏感、金融等调查场景下的交易相关实体。解释交易记录如何与人员、账户、通话、轨迹关联，以及如何用于资金流向分析和可疑交易识别。梳理核心表结构、关键字段（如金额、时间、对方账户、交易类型）、约束和业务规则。给出典型查询示例：按账户/人员查资金流水、大额交易筛选、共同交易分析、相互转账检测、高频交易统计。补充大数据量下的查询优化、事务一致性、敏感字段脱敏和审计日志建议。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,sql/case_table.sql,sql/case_table_1.sql,sql/testSql/交易共同.sql,sql/testSql/全部交易关系.sql,sql/testSql/相互交易.sql",
      "gmt_create": "2026-10-28T07:55:29Z",
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        "sql/case_table.sql",
        "sql/case_table_1.sql",
        "sql/testSql/交易共同.sql",
        "sql/testSql/全部交易关系.sql",
        "sql/testSql/相互交易.sql"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "服务注册中心与健康检查",
      "description": "gateway-registry-and-health",
      "prompt": "创建网关服务注册与健康检查机制的详细文档。解释 GatewayRegistry 如何以 PostgreSQL gateway_service / gateway_node 表为事实来源，维护内存中的 ServiceInfo 列表快照，并在启动阶段通过 seedFromYamlIfNeeded 播种 YAML 配置。说明 reload() 的同步加载、initialized 标志避免初始循环发布 RefreshRoutesEvent，以及 @Scheduled(fixedDelayString=\"${gateway.registry-poll-interval:10s}\") 的多实例对账机制。介绍 ServiceInfo 与 NodeInfo 的数据模型、pathPrefix 匹配、defaultNodeId 的作用。说明 HealthChecker 与 NodeHealthRegistry 如何维护节点 up/down 状态，以及 StickyRouteFilter 如何结合 healthRegistry.isUp 拒绝不可用节点。补充多实例部署时的配置变更传播、性能考虑和故障排查方法。",
      "progress_status": "completed",
      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/registry/GatewayRegistry.java,ai-gateway/src/main/java/com/zsjz/gateway/registry/GatewayConfigRepository.java,ai-gateway/src/main/java/com/zsjz/gateway/registry/ServiceInfo.java,ai-gateway/src/main/java/com/zsjz/gateway/registry/NodeInfo.java,ai-gateway/src/main/java/com/zsjz/gateway/registry/HealthChecker.java,ai-gateway/src/main/java/com/zsjz/gateway/registry/NodeHealthRegistry.java,ai-gateway/src/main/java/com/zsjz/gateway/config/GatewayProperties.java",
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        "ai-gateway/src/main/java/com/zsjz/gateway/registry/ServiceInfo.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/registry/NodeInfo.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/registry/HealthChecker.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/registry/NodeHealthRegistry.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/config/GatewayProperties.java"
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      "name": "技术栈与依赖",
      "description": "technology-stack",
      "prompt": "整理清鉴 AI 调查工具的技术栈与依赖矩阵，分别说明后端、前端和桌面层的框架与核心库。后端使用 Spring Boot 3.5.16、Spring Cloud Gateway WebFlux、MyBatis-Plus、Dynamic Datasource、Sa-Token、Redis、PostgreSQL/pgvector、DJL HuggingFace Tokenizers + ONNX Runtime、DuckDB JDBC、Spring AI Tika、AgentScope。前端使用 Vue 3、Ant Design Vue、Pinia、Vue Router、Vue I18n、Monaco Editor、CodeMirror、VDitor、Markdown-it、ECharts、AntV G6/X6、Relation Graph、MapLibre GL、PMTiles、Dexie、xlsx、crypto-js、dayjs、lodash-es。桌面层使用 Electron 37、electron-builder、ee-core、electron-updater。列出主要依赖版本、用途和兼容性注意事项，说明 Maven 父工程 pom.xml 与前端 package.json 的依赖管理方式，并指出升级依赖时需要注意的风险点。",
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      "gmt_create": "2026-10-28T07:55:29Z",
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      "order": 2,
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        "ai-electron/frontend/package.json",
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        "ai-electron/tsconfig.json"
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      "name": "网关与粘性路由架构",
      "description": "gateway-sticky-routing-architecture",
      "prompt": "创建 Spring Cloud Gateway 粘性路由架构文档。详细解释 StickyRouteFilter 的设计目标：为什么用户会话必须固定到同一 ai-server 节点，过滤器如何在 RouteToRequestUrlFilter 之后重写 GATEWAY_REQUEST_URL_ATTR，并追加 X-Gateway-Node 响应头。说明 LoginRequestFilter 与 LoginResponseFilter 如何配合完成登录前标识和登录后写库绑定；GatewayRegistry、NodeHealthRegistry 等组件如何维护服务/节点注册表与健康状态。画出用户请求经过网关转发到指定 ai-server 的数据流图，说明跨节点切换策略、节点 DOWN 返回 503 的原因，以及 gateway_service / gateway_node 表的作用。补充 CORS、RequestId、错误处理等横切关注点和运维排查要点。",
      "progress_status": "completed",
      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/route/StickyRouteFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginResponseFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginRequestFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/config/CorsConfig.java,ai-gateway/src/main/java/com/zsjz/gateway/GatewayApplication.java,ai-gateway/pom.xml,sql/gateway.sql",
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        "ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginRequestFilter.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/config/CorsConfig.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/GatewayApplication.java",
        "ai-gateway/pom.xml",
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      "name": "添加新模块与新功能",
      "description": "adding-new-module",
      "prompt": "创建添加新模块与新功能的实操指南。说明如何在 ai-server 中添加新的 Spring Boot 业务模块（controller、service、mapper、entity），如何注册到应用上下文，以及如何通过 MyBatis-Plus 访问数据库。说明在 ai-gateway 中新增网关管理接口或过滤器的步骤。说明在前端 App.vue 或路由中注册新页面、新增 IPC 接口时如何修改 preload bridge 和 Electron main.ts。给出完整示例：新增一个查询外部表的后端模块 + 前端页面 + 对应 SQL 初始化脚本。包含 API 版本兼容、配置项扩展、日志记录和测试建议。",
      "progress_status": "completed",
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      "gmt_create": "2026-10-28T07:55:29Z",
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        "ai-electron/frontend/src/App.vue",
        "ai-electron/electron/main.ts",
        "ai-electron/electron/preload/index.ts",
        "sql/gateway.sql"
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      "name": "批量清洗任务",
      "description": "ai-clean-batch-jobs",
      "prompt": "编写 AI 数据清洗中批量清洗任务的详细文档。说明 AiCleanBatch、AiCleanJob、AiRecordCleaner、AiDuckDb、AiRowReader、SheetProbe 等组件的职责和调用关系，解释用户上传 CSV/Excel 后如何解析 Sheet、读取行、匹配清洗模板、执行清洗规则、写入 DuckDB 临时表或目标表，以及如何生成清洗结果和错误记录。详细说明批量任务的生命周期：创建任务、分配 Job、读取数据、执行清洗、收集拒绝记录、更新状态、完成或失败。给出完整的端到端示例：前端上传文件 → 后端创建批量任务 → 选择或自动匹配模板 → 执行清洗 → 查看进度和结果。说明任务状态枚举、失败重试机制、超时处理和并发限制。补充常见问题：批量任务卡住、大文件内存不足、DuckDB 写入失败、模板中途变更、任务状态不一致等。",
      "progress_status": "completed",
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      "gmt_create": "2026-10-28T07:55:29Z",
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        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/entity/AiCleanJob.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/service/AiCleanService.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/service/AiSmartCleanService.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/exec/AiRecordCleaner.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/exec/AiDuckDb.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/probe/AiRowReader.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/probe/SheetProbe.java"
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      "name": "向量存储与检索",
      "description": "knowledge-vector-storage",
      "prompt": "创建知识与向量存储层的详细文档。说明知识文档向量在 pgvector 中的表结构设计、主键与外键关系、向量维度来源、索引类型和查询语句。解释 KnowledgeVectorMapper 提供的插入、更新、删除和相似检索接口，以及它如何被 Agent 的 KnowledgeSearchTool 或 RAG Schema 检索使用。给出向量插入、按相似度 TopK 检索、按文档 ID 删除向量的 SQL/Java 示例。补充向量归一化、余弦距离计算、批量写入、索引刷新策略、向量维度不匹配问题、召回率调优、pgvector 扩展安装和性能监控建议。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/knowledge/mapper/KnowledgeVectorMapper.java,ai-server/src/main/java/com/zsjz/ai/module/knowledge/entity/KnowledgeDoc.java,ai-server/src/main/java/com/zsjz/ai/module/agent/rag/EmbeddingProvider.java,ai-server/src/main/java/com/zsjz/ai/module/agent/tools/KnowledgeSearchTool.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/index/AiCleanTemplateVectorIndex.java,sql/gateway.sql",
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        "ai-server/src/main/java/com/zsjz/ai/module/knowledge/entity/KnowledgeDoc.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/rag/EmbeddingProvider.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/tools/KnowledgeSearchTool.java",
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      "name": "Electron 客户端构建与发布",
      "description": "deployment-electron-client",
      "prompt": "创建 Electron 桌面客户端的构建、打包与发布文档。说明 ai-electron/package.json 中的 scripts：dev、build、start、build-frontend、build-electron、build-w、build-m、build-m-arm64、build-l 等命令的作用和执行顺序，包括前端构建、Electron 构建、ee-bin 加密和 electron-updater 集成。解释 Windows、Linux、macOS 三端打包产物的差异，以及如何通过 pnpm/npm 在 CI 或本地生成安装包。说明前端 bin 目录下的 build.sh、install.sh、startup.*、install.bat、build.bat 脚本用途，以及与 ee-core/electron-builder 的关系。补充客户端自动更新配置、版本号管理、增量更新和回滚注意事项。包含常见问题：Node 版本不匹配、better-sqlite3 重建、前端构建失败、签名/公证失败、更新服务器地址配置错误等。",
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      "name": "多数据源配置与切换",
      "description": "multi-datasource-config",
      "prompt": "编写 MyBatis-Plus + Dynamic Datasource 多数据源配置文档。说明 PostgreSQL/pgvector 作为主业务数据源、DuckDB 作为临时/本地计算数据源的用途差异；解释如何在配置中声明多个数据源，以及在 Service 层按场景切换数据源的方式。描述 pgvector 向量表的使用约束、索引策略和性能注意事项。给出典型用法示例：普通 CRUD 使用默认数据源，批量清洗或临时分析切换到 DuckDB。补充常见问题：数据源选择错误、pgvector 扩展未安装、DuckDB JDBC 连接失败、事务跨数据源限制等。",
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      "prompt": "编写单元测试与 E2E 测试指南。说明后端 JUnit 测试的组织方式，包括 HeaderScorerTest、AiTemplateMatcherTest、AiTemplateMatchEdgeTest、AiCleanSupportTest 等与模板打分、绑定、边缘场景相关的用例；说明 C/D 类 E2E 如何通过 HTTP API 在案件 A=16/B=17 上执行真实清洗链路，并通过 target/aitest_*.py 和 target/aitest/*.json 记录结果。说明 Electron 侧 vitest.config.mts 中 include=['electron/**/*.test.ts'] 和 passWithNoTests=true 的含义，指导如何在主进程新增 .test.ts 单测。补充测试数据隔离、数据库清理、登录态处理、重复上传去重、损坏文件容错等常见测试模式，并给出调试断言失败和定位真实链路问题的步骤。",
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      "prompt": "为 Electron 窗口控制与跨窗口状态同步编写详细文档。重点说明 ai-electron/electron/controller/windowCtl.ts 中的 WindowCtl 类如何作为主进程控制器，提供 openSmartWindow、closeSmartWindow、isSmartWindowOpen、focusMainWindow、getWindowRole、syncState 等 IPC 方法。解释智能工作台窗口与普通主窗口的角色区分（main vs smart），以及 syncState 如何通过 SYNC_EVENT_CHANNEL='app:state' 向除发送者外的所有窗口广播语义事件。说明这些方法与前端 appWindow.ts 的 closeSmartWindow、focusMainWindow、initWindowRole、isSmartWindow 之间的调用关系。给出新增窗口控制方法的示例：后端 controller 方法、前端调用、跨窗口事件监听。包含常见问题：多窗口状态不同步、智能窗口未关闭、主窗口未聚焦、getWindowRole 返回错误角色等。",
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      "name": "AI 数据清洗接口",
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      "prompt": "创建 AI 数据清洗接口的 API 文档，覆盖 /aiClean、/aiClean/synonym 以及 CleanErrorLogController 暴露的接口。说明清洗模板匹配、智能清洗任务、同义词与字段短名映射、批量清洗、清洗结果与错误日志等功能的 REST 接口。对每个接口记录 HTTP 方法、URL、请求参数、响应体、分页字段和错误码；对上传 CSV/Excel 和下载清洗结果的接口，说明文件类型、大小限制、字符编码和进度反馈方式。说明清洗流程与 pgvector、DuckDB 临时数据源的关系，以及清洗失败时如何通过错误日志定位问题。提供 curl 或前端 FormData 调用示例，并给出模板不匹配、字段映射错误、任务失败、向量索引异常等常见问题的排查步骤。",
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      "prompt": "编写前端代码规范与质量工具文档。基于 eslint.config.mjs 说明 ESLint 对 Vue、TypeScript、JavaScript 文件的解析器、插件和规则配置，包括忽略 node_modules/dist/public/build/.git 等路径、Vue 组件规则、TS 宽松规则、Prettier 集成（printWidth=120、semi=true、singleQuote=true、trailingComma=all）。基于 stylelint.config.mjs 说明 Stylelint 对 HTML/Vue/Less/SCSS 的处理，包括 postcss-html、stylelint-config-standard、less/scss 扩展、v-deep/global/deep 伪类伪元素白名单、rpx 单位白名单、inset 禁用和 top/right/bottom/left 允许列表。给出常用命令、IDE 集成建议、常见报错修复方法，以及新增样式语言或 Vue 规则时的扩展方式。",
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      "description": "directory-structure",
      "prompt": "说明仓库顶层目录和各子工程的职责划分。解释 ai-electron 下 electron（主进程、preload、controller、service）、frontend（Vue 3 渲染进程）、public、out、logs、docs 等目录的作用；说明 ai-gateway 中 src/main/java/com/zsjz/gateway 下的路由、过滤器、注册中心和管理接口；说明 ai-server 中 module/* 按业务域划分的 controller/service/mapper/entity 组织结构。结合 pom.xml 和 package.json 解释模块入口文件：ai-electron/electron/main.ts、ai-electron/frontend/src/App.vue、ai-gateway 和 ai-server 的 Spring Boot 入口。补充 SQL、docs、deploy、cmd、data 等非源码目录的使用规范，帮助新成员快速定位代码。",
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      "name": "前端根应用与启动流程",
      "description": "frontend-root-application",
      "prompt": "为前端根应用与启动流程编写详细文档。说明 ai-electron/frontend/src/main.ts 如何初始化 UnoCSS、Ant Design Vue reset 样式、全局设计样式、AI 模块样式，然后创建 Vue 应用、注册全局组件、国际化、路由、Store、错误处理、Tab 监听补丁和弹窗行为补丁。解释启动探测逻辑 waitForBackendReady：最多重试 10 次、每次间隔约 3 秒，调用 healthApi 探测后端是否就绪，并在 loading 页显示重试提示、重连按钮和服务地址设置入口。说明 App.vue 如何配置 Ant Design Vue 主题、语言、AppProvider，并通过 authorizationInfoApi 获取授权单元，写入水印。解释 isServerSetupMissing、getApiOrigin、PageEnum.BASE_AUTHORIZATION、PageEnum.BASE_SERVER_SETUP 在启动路由和授权判断中的作用。给出新增全局初始化逻辑、启动探测扩展、授权缓存处理的示例。包含常见问题：后端连接失败、loading 卡住、授权信息不显示、路由跳转到 404、服务地址为空等。",
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      "dependent_files": "ai-electron/frontend/src/App.vue,ai-electron/frontend/src/main.ts,ai-electron/frontend/src/core/settings/serverSetting.ts,ai-electron/frontend/src/core/api/sys/login.ts",
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      "prompt": "创建清鉴客户端卸载与数据清理指南。说明 cmd/uninstall.bat（Windows）和 cmd/uninstall.sh（Linux/macOS）卸载脚本的功能：强制终止 qingjian-client 进程、递归删除 ~/.config/qingjian-client、~/.local/share/QingJian、~/.qingjian-client 等用户数据目录。解释 Linux 脚本的安全检查逻辑（$HOME 判空、pkill 返回值、rm -rf 权限问题提示），以及 Windows 批处理对应的清理范围。提供管理员权限执行方法、卸载前备份建议和数据恢复注意事项。补充手动清理清单：浏览器缓存中的服务地址、Electron AppData、临时文件、残留进程和注册表项（如适用）。包含常见问题：进程无法终止、权限不足、部分目录未被删除、卸载后仍显示旧授权信息等的处理方法。",
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      "prompt": "创建开发者调试与问题排查指南。覆盖常见问题定位路径：Gateway 粘性路由无法绑定用户、登录成功后仍 503、Agent SSE 断连或心跳异常、pgvector 向量检索无结果、地图加载失败、许可证校验失败、Electron 主进程崩溃、前端资源加载异常。说明如何查看服务端日志、网关日志、Electron 控制台和网络请求。给出 StickyRouteFilter 中 token/username 解析、节点选择、URL 重写和 X-Gateway-Node 响应头的检查方法。说明如何验证 Agent LLM 调用、RAG Schema 检索、Python 执行器和附件上传。提供诊断清单、复现步骤和恢复建议。",
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      "prompt": "编写 Electron 桌面端安全边界与本地文件保护文档。说明主进程、preload 桥接、渲染进程之间的权限隔离模型，preload bridge 暴露给前端的能力边界，以及为什么不应直接暴露 Node/Electron API。说明敏感配置、服务地址、token、工作区目录、地图资源、PMTiles 文件的本地存储位置和访问控制。结合窗口控制器 windowCtl 说明窗口创建、URL 白名单、弹窗限制等安全措施。给出本地文件泄露、恶意 HTML 视图加载、跨域读取等安全风险及防护建议。",
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      "name": "工具包、Python 执行器与 Artifact",
      "description": "agent-tools-python-artifacts",
      "prompt": "为工具包、Python 执行器与 Artifact 创建详细文档。说明 AgentTool、AgentToolPackEntity、AgentToolRegistry 构成的工具目录体系，AgentToolCatalogService 如何加载和匹配工具，以及 AgentPythonFileController 提供的 Python 文件上传与管理能力。解释 AgentArtifactController 如何管理 Agent 生成的附件、中间文件或可视化结果，以及前端 artifacts.ts 如何展示这些产物。给出示例：注册新工具、调用 Python 脚本、上传数据文件、查看工具调用结果和 Artifact 预览。补充常见问题：Python 执行权限不足、脚本超时、工具未注册、Artifact 路径不存在、并发访问冲突等。",
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      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/agent/tools/AgentToolRegistry.java,ai-server/src/main/java/com/zsjz/ai/module/agent/entity/AgentTool.java,ai-server/src/main/java/com/zsjz/ai/module/agent/service/AgentToolCatalogService.java,ai-server/src/main/java/com/zsjz/ai/module/agent/service/impl/AgentToolCatalogServiceImpl.java,ai-server/src/main/java/com/zsjz/ai/module/agent/entity/AgentToolPackEntity.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentToolPackController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentPythonFileController.java,ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentArtifactController.java,ai-electron/frontend/src/ai/api/capabilityApi.ts,ai-electron/frontend/src/ai/utils/artifacts.ts",
      "gmt_create": "2026-10-28T07:55:29Z",
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        "ai-server/src/main/java/com/zsjz/ai/module/agent/entity/AgentTool.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/service/AgentToolCatalogService.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/service/impl/AgentToolCatalogServiceImpl.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/entity/AgentToolPackEntity.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentToolPackController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentPythonFileController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/controller/AgentArtifactController.java",
        "ai-electron/frontend/src/ai/api/capabilityApi.ts",
        "ai-electron/frontend/src/ai/utils/artifacts.ts"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "轨迹模块 track",
      "description": "business-track",
      "prompt": "为轨迹模块 track 创建详细文档。说明该模块管理快递、同行、同住、同城、基站、火车票等轨迹类调查数据，帮助还原目标人员的时间线和空间活动。解释轨迹数据与人员 person、通话 call、交易 trans 的关联方式，以及在案件串并、行踪追踪中的作用。梳理各轨迹类型的实体结构、时间戳、地理位置字段、来源系统标识和清洗规则。给出查询示例：按人员和时间范围查轨迹、同行/同住关系挖掘、基站热点分析、跨系统轨迹合并。补充地理信息查询优化、时间窗口过滤、轨迹去重和可视化对接建议。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,sql/case_table.sql,sql/case_table_1.sql,sql/testSql/轨迹测试.sql",
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        "sql/case_table_1.sql",
        "sql/testSql/轨迹测试.sql"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "认证与会话管理",
      "description": "authentication-session",
      "prompt": "编写基于 Sa-Token 的认证与会话管理文档。说明用户登录流程、Token 生成与校验、会话状态在 Redis 中的存储方式，以及客户端 x-token 如何与服务端会话关联。解释与网关 StickyRouteFilter 的协作关系：Gateway 负责按用户名绑定节点，ai-server 负责实际 Token 校验。描述账号被顶下线/踢下线后释放案件数据源的行为，以及登录失效时前端清理缓存的注意事项。补充安全建议：Token 泄露处理、会话超时配置、敏感接口鉴权模式和调试方法。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,ai-server/src/main/java/com/zsjz/ai/",
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      "parent_id": "1721b548-ae66-4730-9aba-43ab062f7390",
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      "order": 3,
      "kk_dependent_files": [
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    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "清洗结果与统计",
      "description": "ai-clean-results-and-stats",
      "prompt": "编写 AI 数据清洗中清洗结果与统计的详细文档。说明 AiRowCleanResult、AiRejectRecord、ColumnError、AiRejectReason 等模型的结构和用途，解释成功行、拒绝行、列级错误、拒绝原因分类之间的关系。详细说明清洗结果如何持久化、如何统计行数、成功数、拒绝数和各类错误分布，以及 ai_clean_row_stats.sql 对应的统计设计。给出查看清洗结果、导出成功数据和错误数据的示例，包括前端 case 目录中与清洗结果展示相关的界面交互。说明结果数据的保留策略、清理时机和性能考虑。补充常见问题：结果为空但任务成功、拒绝记录缺失、错误列信息不准确、统计数据延迟、导出文件过大等。",
      "progress_status": "completed",
      "dependent_files": "sql/ai_clean_row_stats.sql,ai-server/src/main/java/com/zsjz/ai/module/aiclean/model/AiRowCleanResult.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/model/AiRejectRecord.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/model/ColumnError.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/exec/AiRejectCollector.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/enums/AiRejectReason.java,ai-electron/frontend/src/case/",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "kk_dependent_files": [
        "sql/ai_clean_row_stats.sql",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/model/AiRowCleanResult.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/model/AiRejectRecord.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/model/ColumnError.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/exec/AiRejectCollector.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/enums/AiRejectReason.java",
        "ai-electron/frontend/src/case/"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "嵌入调试接口",
      "description": "embedding-debug-interface",
      "prompt": "创建嵌入调试接口的详细文档。说明 EmbeddingDebugController.debug 如何通过 EmbeddingService 调用本地 ONNX 推理引擎 OnnxEmbeddingEngine，对一批输入文本生成向量、计算两两余弦相似度矩阵，并返回维度、耗时、向量数组和相似度矩阵。明确该接口只用于验证本地 embedding 模型是否正常，不参与业务路由。提供 EmbeddingDebugDTO 和 EmbeddingDebugVO 的请求/响应 JSON 示例，说明 dimension、embedMillis、vectors[]、similarity[][] 的含义。补充 ONNX 模型加载、向量维度配置、归一化行为、批量大小、内存占用、CPU/GPU 性能、调试结果解读和模型部署故障排查指南。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/embedding/controller/EmbeddingDebugController.java,ai-server/src/main/java/com/zsjz/ai/module/embedding/service/EmbeddingService.java,ai-server/src/main/java/com/zsjz/ai/module/embedding/core/OnnxEmbeddingEngine.java,ai-server/src/main/java/com/zsjz/ai/module/embedding/config/EmbeddingProperties.java,ai-server/src/main/java/com/zsjz/ai/module/embedding/vo/EmbeddingDebugVO.java,ai-server/src/main/java/com/zsjz/ai/module/embedding/dto/EmbeddingDebugDTO.java",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "kk_dependent_files": [
        "ai-server/src/main/java/com/zsjz/ai/module/embedding/controller/EmbeddingDebugController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/embedding/service/EmbeddingService.java",
        "ai-server/src/main/java/com/zsjz/ai/module/embedding/core/OnnxEmbeddingEngine.java",
        "ai-server/src/main/java/com/zsjz/ai/module/embedding/config/EmbeddingProperties.java",
        "ai-server/src/main/java/com/zsjz/ai/module/embedding/vo/EmbeddingDebugVO.java",
        "ai-server/src/main/java/com/zsjz/ai/module/embedding/dto/EmbeddingDebugDTO.java"
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    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "网关管理接口",
      "description": "admin-api",
      "prompt": "创建网关管理接口的 API 文档。覆盖 /gateway/admin/status、/services、/nodes、/routes/bind、/routes/unbind、/routes/import-existing、/reload 等端点，说明 HTTP 方法、URL 模式、请求体结构、响应格式 ApiResult<Object> 和管理员认证要求（AdminAuthWebFilter）。解释 AdminService 如何封装 createService/updateService/deleteService、createNode/updateNode/deleteNode、checkNode、pageRoutes、bindRoute、unbind、importExisting、reload 等操作，并说明这些操作如何通过 GatewayRegistry.reload() 触发路由刷新。补充 IP 白名单控制、阻塞 JDBC 调用通过 Schedulers.boundedElastic 保护 Netty 事件循环的原因，以及 AdminApiException 和 WebExchangeBindException 的错误响应格式。提供典型运维场景示例，如新增 ai-server 节点、绑定路由、导入已有路由、手动重载配置。",
      "progress_status": "completed",
      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/admin/AdminController.java,ai-gateway/src/main/java/com/zsjz/gateway/admin/AdminService.java,ai-gateway/src/main/java/com/zsjz/gateway/admin/AdminAuthWebFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/support/ApiResult.java,ai-gateway/src/main/java/com/zsjz/gateway/support/AdminApiException.java",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "parent_id": "198e92ee-5762-48f9-835d-17889a315be1",
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      "order": 3,
      "kk_dependent_files": [
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        "ai-gateway/src/main/java/com/zsjz/gateway/admin/AdminService.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/admin/AdminAuthWebFilter.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/support/ApiResult.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/support/AdminApiException.java"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "后端服务架构",
      "description": "backend-service-architecture",
      "prompt": "创建 ai-server 后端服务架构文档。说明 Spring Boot 应用入口、模块化组织原则（plat/agent/aiclean/knowledge/graph/person/call/trans/track/govern/search/dm/otg/external/embedding），以及每个模块在调查场景中的职责。重点描述多数据源配置：MyBatis-Plus + Dynamic Datasource 如何同时连接 PostgreSQL/pgvector、Redis、DuckDB 等业务与临时数据源；Sa-Token 认证流程、SSE 心跳保活机制、定时任务与工作空间清理。结合 AgentScope RAG、向量检索、Python 执行器、附件与 Workspace Catalog，说明 agent 模块与其他模块的协作方式。补充异常处理、日志、性能考虑和多节点扩展建议。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,ai-server/src/main/java/com/zsjz/ai/App.java,ai-server/src/main/resources/application.yml,ai-server/src/main/resources/application-dev.yml,ai-server/src/main/resources/application-prod.yml",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "a4b69928-d9a2-469a-8611-d8167311ed51",
      "layer_level": 1,
      "order": 3,
      "kk_dependent_files": [
        "ai-server/pom.xml",
        "ai-server/src/main/java/com/zsjz/ai/App.java",
        "ai-server/src/main/resources/application.yml",
        "ai-server/src/main/resources/application-dev.yml",
        "ai-server/src/main/resources/application-prod.yml"
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    },
    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "AI 数据清洗模板、同义词与行统计表",
      "description": "ai-clean-schemas",
      "prompt": "创建 AI 数据清洗功能的数据库设计文档，重点说明 ai_clean 清洗模板、ai_clean_field_short_names 字段短名映射、ai_clean_row_stats 清洗行统计、ai_clean_synonym_init 同义词初始化等相关表。详细描述模板定义、字段映射规则、同义词词库、清洗结果统计字段的数据类型、主外键、索引和业务约束。解释清洗流程中的数据来源、模板匹配、同义词替换、字段映射和结果落库的数据流。提供清洗任务查询、统计聚合、模板维护的典型 SQL 示例，并说明批量清洗的性能优化、重复执行去重和数据回滚方案。",
      "progress_status": "completed",
      "dependent_files": "sql/ai_clean.sql,sql/ai_clean_field_short_names.sql,sql/ai_clean_row_stats.sql,sql/ai_clean_synonym_init.sql",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "c1789760-0a39-4847-879e-bd14a1ed7b37",
      "layer_level": 1,
      "order": 3,
      "kk_dependent_files": [
        "sql/ai_clean.sql",
        "sql/ai_clean_field_short_names.sql",
        "sql/ai_clean_row_stats.sql",
        "sql/ai_clean_synonym_init.sql"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "关键数据流与应用生命周期",
      "description": "data-flow-and-lifecycle",
      "prompt": "创建清鉴 AI 调查工具的关键数据流与应用生命周期文档。以典型用户工作流为主线，逐步说明：客户端启动 → 读取 localStorage 中的服务地址 → 调用 /sys/info 获取授权单元 → 用户登录 → Gateway 解析 username/token 选择并绑定 ai-server 节点 → 后续请求通过 StickyRouteFilter 稳定转发 → ai-server 校验 Sa-Token 会话 → Agent 调用 LLM 与 pgvector 向量检索 → 图谱/统计结果返回前端渲染。绘制时序图和状态图，标注跨进程、跨网络、跨服务的边界。解释 SSE 心跳保活、登录失效、节点不可用、Agent 流式响应等异常情况下的数据流变化，并给出排查思路。",
      "progress_status": "completed",
      "dependent_files": "ai-electron/electron/main.ts,ai-electron/frontend/src/App.vue,ai-gateway/src/main/java/com/zsjz/gateway/route/StickyRouteFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginResponseFilter.java,ai-server/pom.xml",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "parent_id": "a4b69928-d9a2-469a-8611-d8167311ed51",
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      "order": 4,
      "kk_dependent_files": [
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        "ai-electron/frontend/src/App.vue",
        "ai-gateway/src/main/java/com/zsjz/gateway/route/StickyRouteFilter.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginResponseFilter.java",
        "ai-server/pom.xml"
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    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "SSE 心跳与长连接保活",
      "description": "sse-heartbeat",
      "prompt": "编写 SSE Server-Sent Events 心跳与长连接保活文档。说明 Agent 流式对话、心跳任务、服务端定时保活机制的工作流程，以及客户端如何处理断连、重连和消息乱序。解释 SSE 与 WebSocket 的区别在本项目中的选型原因，并说明长连接对服务器资源的影响。提供调试技巧：查看服务端日志、检查心跳间隔、确认防火墙/Nginx 是否支持 SSE。补充性能优化建议：连接池控制、超时清理、背压处理和异常恢复策略。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,ai-server/src/main/java/com/zsjz/ai/",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "parent_id": "1721b548-ae66-4730-9aba-43ab062f7390",
      "layer_level": 1,
      "order": 4,
      "kk_dependent_files": [
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    },
    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "网关基础设施与异常处理",
      "description": "gateway-infrastructure",
      "prompt": "创建网关基础设施层文档，覆盖 GatewayApplication 应用入口、CorsConfig 跨域配置、WebClientConfig 响应式 WebClient 配置、RequestIdFilter 的请求 ID 注入、GatewayErrorHandler 的全局异常处理，以及 StickyUnavailableException 的统一错误语义。说明这些组件如何支撑粘性路由、管理接口和业务转发，特别是 503 错误在不同场景下的含义：服务不存在、服务停用、无可用节点、绑定节点不可用、用户未绑定节点等。补充 Netty/WebFlux 环境下的注意事项，例如避免阻塞 IO、合理使用调度器、SSE 心跳与长连接兼容性。提供排障清单，帮助定位 CORS 拦截、WebClient 超时、全局异常未捕获、请求 ID 缺失等问题。",
      "progress_status": "completed",
      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/support/RequestIdFilter.java,ai-gateway/src/main/java/com/zsjz/gateway/support/GatewayErrorHandler.java,ai-gateway/src/main/java/com/zsjz/gateway/support/StickyUnavailableException.java,ai-gateway/src/main/java/com/zsjz/gateway/config/CorsConfig.java,ai-gateway/src/main/java/com/zsjz/gateway/config/WebClientConfig.java,ai-gateway/src/main/java/com/zsjz/gateway/GatewayApplication.java",
      "gmt_create": "2026-10-28T07:55:29Z",
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        "ai-gateway/src/main/java/com/zsjz/gateway/support/GatewayErrorHandler.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/support/StickyUnavailableException.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/config/CorsConfig.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/config/WebClientConfig.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/GatewayApplication.java"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "授权单元与水印",
      "description": "desktop-authorization-watermark",
      "prompt": "为桌面客户端授权单元与水印机制编写详细文档。说明 App.vue 如何通过 authorizationInfoApi 获取服务端授权信息，使用 extractAuthorizationCache 解析 authorizationLabel、overDateTime、authorizationUnit，并写入 userStore 页面缓存。解释 useWatermark 如何根据 authorizationUnit 动态设置页面水印，并在授权信息为空时清除水印。说明 license.ts 中授权缓存提取、过期判断和过期消息生成逻辑，以及与 login.ts 中 checkAuthApi、authorizationInfoApi 的关系。给出新增授权字段、扩展水印内容、处理授权过期的示例。包含常见问题：授权信息未加载、水印不显示、授权过期仍可使用、localStorage 缓存不一致、授权信息与网关 token 不一致等。",
      "progress_status": "completed",
      "dependent_files": "ai-electron/frontend/src/App.vue,ai-electron/frontend/src/core/utils/license.ts,ai-electron/frontend/src/core/store/modules/case.ts,ai-electron/frontend/src/core/hooks/web/useWatermark.ts,ai-electron/frontend/src/core/api/sys/login.ts",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "parent_id": "d36adb59-0865-4057-ac6b-1a3762816c01",
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      "order": 4,
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        "ai-electron/frontend/src/core/store/modules/case.ts",
        "ai-electron/frontend/src/core/hooks/web/useWatermark.ts",
        "ai-electron/frontend/src/core/api/sys/login.ts"
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    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "系统架构设计",
      "description": "system-architecture",
      "prompt": "创建清鉴 AI 调查工具的系统架构文档，描述高层分层模型：Electron 客户端 → Preload Bridge → Spring Cloud Gateway → ai-server 业务模块 → PostgreSQL/pgvector/Redis/文件系统。重点解释粘性路由的设计目标：为什么用户会话必须固定到同一 ai-server 节点，StickyRouteFilter 如何在 RouteToRequestFilter 之后重写目标 URL，以及 LoginResponseFilter 如何实现登录成功后写库绑定。画出客户端、网关、服务、数据库之间的交互图和数据流向图。说明跨进程安全隔离、SSE 心跳保活、动态数据源切换、AgentScope RAG 调用等横切关注点。讨论可扩展性（多 ai-server 节点）、容错策略（节点 DOWN 返回 503）和部署拓扑。",
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      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/route/StickyRouteFilter.java,ai-electron/electron/main.ts,ai-electron/frontend/src/App.vue,ai-server/pom.xml,ai-gateway/pom.xml",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "order": 4,
      "kk_dependent_files": [
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        "ai-electron/electron/main.ts",
        "ai-electron/frontend/src/App.vue",
        "ai-server/pom.xml",
        "ai-gateway/pom.xml"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "知识库与嵌入调试接口",
      "description": "knowledge-and-embedding-api",
      "prompt": "创建知识库与嵌入调试接口的 API 文档，覆盖 KnowledgeBaseController 和 EmbeddingDebugController。说明知识库文档的创建、查询、更新、删除、向量入库、下载日志等接口，以及嵌入调试接口的输入输出格式。记录每个接口的 HTTP 方法、URL、请求参数、响应体、错误码和权限要求。说明知识库与 Agent RAG 中向量检索的关系，以及 embedding 调试接口如何辅助排查向量化质量。提供 curl 示例，并说明文档解析失败、向量入库失败、相似度检索为空等问题的排查方法。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/knowledge/controller/KnowledgeBaseController.java,ai-server/src/main/java/com/zsjz/ai/module/embedding/controller/EmbeddingDebugController.java",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "order": 4,
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        "ai-server/src/main/java/com/zsjz/ai/module/embedding/controller/EmbeddingDebugController.java"
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    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "清洗模板向量索引",
      "description": "ai-clean-vector-index",
      "prompt": "编写 AI 数据清洗中清洗模板向量索引的详细文档。说明 AiCleanTemplateVectorIndex、AiCleanVectorProperties 的职责，解释模板如何通过向量化进入 pgvector 或向量检索链路，并与 AiTemplateMatcher、HeaderScorer 协同提升模板匹配准确率。详细说明向量索引的构建时机、刷新策略、元数据字段、相似度阈值和回退逻辑。给出向量索引配置、重建索引、验证匹配效果的示例。说明向量索引与传统规则匹配的优先级关系，以及在模板数量增长时的性能影响。补充常见问题：向量索引缺失、相似度阈值过高或过低、模板变更后索引未更新、pgvector 不可用时降级行为等。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/aiclean/index/AiCleanTemplateVectorIndex.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/index/AiCleanVectorProperties.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/match/AiTemplateMatcher.java,ai-server/src/main/java/com/zsjz/ai/module/aiclean/match/HeaderScorer.java,ai-server/src/test/java/com/zsjz/ai/module/aiclean/index/AiCleanTemplateVectorIndexTest.java",
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        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/index/AiCleanVectorProperties.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/match/AiTemplateMatcher.java",
        "ai-server/src/main/java/com/zsjz/ai/module/aiclean/match/HeaderScorer.java",
        "ai-server/src/test/java/com/zsjz/ai/module/aiclean/index/AiCleanTemplateVectorIndexTest.java"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "治理模块 govern",
      "description": "business-govern",
      "prompt": "为治理模块 govern 创建详细文档。说明该模块负责治理树、治理配置和结果处理器，支撑调查场景中的人员关系治理、实体归一、标签体系和分析结果结构化。解释治理树如何作为业务分类或关系拓扑，驱动下游 agent、图谱、清洗和外部表的处理逻辑。梳理治理树节点结构、父子关系、状态、扩展字段及配置项。给出使用示例：定义治理树、绑定治理规则、执行治理任务、查看治理结果。说明治理结果如何被 search、dm、otg 和其他业务模块消费，并提供扩展新治理规则和结果处理器的指导。",
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      "dependent_files": "ai-server/pom.xml,sql/case_table.sql,sql/case_table_1.sql,sql/insight_agent_tables.sql",
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      "parent_id": "8f78a451-8218-40a1-9474-b29ba3fd8dca",
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      "order": 4,
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        "sql/insight_agent_tables.sql"
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    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "多节点扩展与负载均衡",
      "description": "deployment-multi-node-scaling",
      "prompt": "创建多节点 ai-server 扩展与负载均衡方案。说明粘性路由的设计目标：同一用户请求始终路由到同一 ai-server 节点，避免跨节点访问本地磁盘和会话状态不一致。解释 StickyRouteFilter 如何从 token/username 解析 userId，查找绑定节点并重写目标 URL，同时附加 X-Gateway-Node 响应头。说明服务注册中心、节点健康检查、LoginResponseFilter 登录绑定机制，以及节点 DOWN 时返回 503 不自动切换到其他节点的约束。给出多节点部署拓扑图：多个 ai-server 实例共享 PostgreSQL/pgvector/Redis，单个或集群式 ai-gateway 做粘性转发。补充水平扩展建议：节点扩容策略、登录顶号与会话释放、DuckDB 最大案件数与内存比例调整、向量索引重建成本、ES/Neo4j 共享配置。包含监控与排障：节点健康状态查询、粘性路由失效、登录绑定错乱、Redis 热点键、数据库连接池耗尽等问题的定位方法。",
      "progress_status": "completed",
      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/route/StickyRouteFilter.java,ai-gateway/pom.xml,deploy/env.sh",
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      "parent_id": "67aa6a8d-c25c-435e-be2c-9a5fda6668b7",
      "layer_level": 1,
      "order": 4,
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        "ai-gateway/pom.xml",
        "deploy/env.sh"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "许可证与认证问题排查",
      "description": "license-troubleshooting",
      "prompt": "编写许可证与认证问题的综合排查指南。涵盖以下场景：regInfo.exe 无法执行或返回异常、机器码不一致、许可证过期、授权单元为空；x-token 丢失或与其他节点不一致导致 401/403；Gateway 未绑定节点或节点健康检查失败；账号被顶下线后仍持有旧 token；服务端重启后会话丢失。对每个场景给出复现步骤、关键日志位置、需要检查的配置项、数据库表字段、网关转发结果和修复方案。提供快速诊断清单和常见问题 FAQ。",
      "progress_status": "completed",
      "dependent_files": "readme.md,ai-gateway/src/main/java/com/zsjz/gateway/route/StickyRouteFilter.java,ai-electron/frontend/src/App.vue",
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      "parent_id": "c77f0da0-55bc-4f69-9e32-f4aca699b57c",
      "layer_level": 1,
      "order": 4,
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        "ai-electron/frontend/src/App.vue"
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    },
    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "案件表与外部表结构",
      "description": "case-and-external-tables",
      "prompt": "创建案件表和外部表结构的数据库设计文档。说明 case_table、case_table_1、table_data_1 等案件数据源表，以及 external_tables、external_table_field 等外部表定义和字段映射表。详细描述表之间的关系：用户/案件、案件与表、表与字段、表数据快照之间的关系。解释外部表在调查场景中如何承载通话、交易、轨迹、人员、车辆违法、罪犯等扩展实体。给出 ER 图、关键字段定义、索引设计和查询模式，包括按案件查询、按外部表查询、字段枚举值查询等。补充数据版本、迁移规范、删除策略和安全访问控制建议。",
      "progress_status": "completed",
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      "gmt_create": "2026-10-28T07:55:29Z",
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "Insight 工作区与 Workspace Catalog",
      "description": "agent-insight-workspace",
      "prompt": "为 Insight 工作区与 Workspace Catalog 创建详细文档。说明 AgentInsightSession 与 AgentInsightMessage 的数据模型，InsightAgentFactory 如何启动分析型 Agent，以及前端 useInsightStream 如何通过 SSE 消费 Insight 流式输出。解释 Workspace Catalog 与案件数据源、用户会话之间的关系，说明 Insight 与普通 Agent 对话的区别：是否持久化、是否承载图谱分析结果、是否与 graph/insight API 联动。给出示例：创建 Insight 会话、关联图谱或外部数据、查看 Insight 消息流、清理工作区。补充常见问题：Insight 会话丢失、消息未落库、工作区跨节点不一致、SSE 流被网关切断等。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/agent/insight/entity/AgentInsightMessage.java,ai-server/src/main/java/com/zsjz/ai/module/agent/insight/entity/AgentInsightSession.java,ai-server/src/main/java/com/zsjz/ai/module/agent/insight/mapper/AgentInsightMessageMapper.java,ai-server/src/main/java/com/zsjz/ai/module/agent/insight/mapper/AgentInsightSessionMapper.java,ai-server/src/main/java/com/zsjz/ai/module/agent/insight/agent/InsightAgentFactory.java,ai-electron/frontend/src/graph/insight/hooks/useInsightStream.ts,ai-electron/frontend/src/graph/insight/types.ts,ai-electron/frontend/src/graph/insight/api.ts",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "layer_level": 1,
      "order": 4,
      "kk_dependent_files": [
        "ai-server/src/main/java/com/zsjz/ai/module/agent/insight/entity/AgentInsightMessage.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/insight/entity/AgentInsightSession.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/insight/mapper/AgentInsightMessageMapper.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/insight/mapper/AgentInsightSessionMapper.java",
        "ai-server/src/main/java/com/zsjz/ai/module/agent/insight/agent/InsightAgentFactory.java",
        "ai-electron/frontend/src/graph/insight/hooks/useInsightStream.ts",
        "ai-electron/frontend/src/graph/insight/types.ts",
        "ai-electron/frontend/src/graph/insight/api.ts"
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "图谱与图表接口",
      "description": "graph-and-chart-api",
      "prompt": "创建图谱与图表接口的 API 文档，覆盖 GraphController 暴露的 REST 接口。说明关系图数据的查询、生成、导出等接口的 HTTP 方法、URL、请求参数、响应体结构和错误码。描述图谱数据与人员、通话、交易、轨迹等业务实体之间的关系，以及 AntV G6/X6、Relation Graph、ECharts 在前端的渲染方式。说明大数据量图谱的性能注意事项，例如分页、过滤条件和导出格式。提供 curl 和前端调用示例，并给出图谱数据为空、节点过多导致卡顿、导出失败等问题的排查方法。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/graph/controller/GraphController.java",
      "gmt_create": "2026-10-28T07:55:29Z",
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      "parent_id": "14469378-a6de-4dcb-907f-1edc16463b71",
      "layer_level": 1,
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      "kk_dependent_files": [
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      "name": "日志、监控与故障排查",
      "description": "deployment-monitoring-troubleshooting",
      "prompt": "创建部署后的日志收集、监控指标与故障排查手册。说明 ai-gateway 和 ai-server 的标准日志位置、输出格式、按模块分类的建议，以及 Electron 客户端主进程日志、渲染进程控制台和 electron-updater 日志。列出关键监控指标：PostgreSQL/pgvector 连接数与慢查询、Redis 命中率与内存、Elasticsearch 索引状态、Neo4j 连接、DuckDB 打开案件数、向量模型加载时间、Agent SSE 心跳、文件上传大小、登录成功率。说明如何使用 Spring Actuator、系统监控工具或外部 APM 采集这些指标。提供常见故障排查清单：登录后 503、跨域失败、Agent 对话无响应、RAG 向量检索为空、清洗模板匹配失败、离线地图 PMTiles 加载失败、许可证校验失败、自动更新失败、进程卡死等。对每个问题给出现象、可能原因、定位步骤和修复建议，并关联 deploy/env.sh 中相关配置项。补充备份与恢复建议：PostgreSQL/pgvector 全量与增量备份、Redis 持久化、本地文件存储归档、客户端用户数据目录迁移。",
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      "name": "搜索模块 search",
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      "prompt": "为搜索模块 search 创建详细文档。说明该模块提供文档索引、全文检索、查询服务和初始化器，用于加速对案件数据、Agent 内容、清洗结果和知识库的检索。解释搜索服务与 PostgreSQL/pgvector 的关系，以及是否结合向量检索或传统全文索引。梳理索引模型、分词策略、查询语法、权重和分页机制。给出示例：关键词搜索、按案件/用户维度过滤、搜索结果高亮、增量索引更新。补充搜索性能调优、索引重建、缓存策略和与 Agent RAG 集成的注意事项。",
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      "prompt": "创建 pgvector 向量表与 DuckDB 临时数据源的数据库设计说明。说明项目中哪些表使用 PostgreSQL + pgvector 存储向量嵌入，用于 Agent RAG、知识库相似检索和意图识别；哪些场景使用 DuckDB JDBC 作为临时数据源进行本地分析或测试。对比两种数据源的设计目标、数据类型、索引策略和生命周期。给出向量维度、相似度检索参数、更新与重建索引的注意事项。说明临时数据与持久化业务数据的边界，以及清理策略、备份恢复和性能调优建议。若仓库中存在具体的 pgvector 建表脚本或向量表命名约定，应一并记录。",
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      "name": "桌面客户端",
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      "prompt": "为 Electron 桌面客户端编写详细文档。说明主进程生命周期（ai-electron/electron/main.ts）、preload 桥接的安全模型（bridge.ts、index.ts）、窗口控制器（windowCtl.ts）和服务封装。解释前端根组件 App.vue 如何初始化主题、国际化、水印和授权单元，以及 main.ts 如何挂载应用。说明客户端与服务端地址绑定、localStorage 缓存、自动更新（electron-updater）、离线地图（MapLibre GL + PMTiles china.pmtiles）和 regInfo.exe 许可证校验的基本流程。给出新增页面、组件、IPC 接口和 Electron service 的示例。包含常见问题：主进程崩溃、preload 权限不足、地图加载失败、授权信息不显示等。",
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        "ai-electron/electron/controller/windowCtl.ts",
        "ai-electron/electron/service/window/",
        "ai-electron/frontend/src/App.vue",
        "ai-electron/frontend/src/main.ts",
        "ai-electron/package.json",
        "ai-electron/frontend/package.json"
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      "description": "desktop-offline-map",
      "prompt": "为离线地图与 PMTiles 配置编写详细文档。说明前端如何使用 MapLibre GL 和 PMTiles 加载本地 china.pmtiles，offlineMap.ts 中如何构建瓦片源、加载 style（如 behavior-spacetime-style.json），以及 MapLocalSettingModal.vue 如何管理地图本地路径、样式切换和配置保存。结合 readme.md 中关于栅格地图配置、激活命令和 regInfo.exe 的说明，解释许可证校验与地图加载之间的关系：只有许可证有效时才允许加载离线地图数据。说明地图服务的初始化时机、资源目录 public/resource/map 的结构、以及如何替换其他 PMTiles 文件或样式。给出新增地图图层、更换离线地图源、调试地图加载失败的示例。包含常见问题：china.pmtiles 无法加载、样式 JSON 报错、地图空白、许可证无效导致地图禁用、PMTiles 路径错误等。",
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      "name": "定时任务与工作空间清理",
      "description": "scheduled-tasks-workspace-cleanup",
      "prompt": "编写定时任务与工作空间清理文档。说明系统启动后用于清理 Agent Workspace、临时文件、下载日志、索引残留等任务的调度策略和执行频率。解释工作空间的目录结构、生命周期、与用户/会话的关系，以及清理失败时的重试或告警策略。给出运维操作建议：调整清理周期、监控磁盘占用、定位无法删除的文件。补充故障排查：任务未执行、权限不足、路径不存在、清理过于激进导致正在使用的文件丢失等。",
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      "name": "网关粘性路由",
      "description": "gateway-sticky-routing",
      "prompt": "创建网关粘性路由的详细文档。解释 StickyRouteFilter 的核心逻辑：如何从请求 token/username 解析 userId，查找已绑定的 ai-server 节点，重写 GATEWAY_REQUEST_URL_ATTR 并追加 X-Gateway-Node 响应头。说明 LoginResponseFilter 在登录成功后如何将用户绑定到具体服务节点，LoginRequestFilter 如何标记登录请求。介绍 GatewayRegistry 的服务/节点注册表内存快照与定时对账机制、NodeHealthRegistry 的健康检查、CORS 配置、RequestIdFilter 和 GatewayErrorHandler。补充网关管理接口、503 错误处理、节点下线时的行为，以及调试粘性路由问题的方法。",
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      "order": 6,
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        "ai-gateway/src/main/java/com/zsjz/gateway/filter/LoginRequestFilter.java",
        "ai-gateway/src/main/java/com/zsjz/gateway/GatewayApplication.java",
        "sql/gateway.sql"
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      "name": "数据建模模块 dm",
      "description": "business-dm",
      "prompt": "为数据建模模块 dm 创建详细文档。说明该模块负责数据建模、文件识别、AI 画像、边配置和清理错误日志，是连接原始数据与业务查询的重要中间层。解释 dm 如何通过文件识别推断表结构、生成 AI 画像、定义实体间边关系，并将结果持久化供 graph、agent、aiclean 等模块使用。梳理建模元数据模型、文件上传识别流程、画像字段映射、边配置结构和错误日志格式。给出示例：上传 CSV/Excel 进行自动建模、配置实体边、查看 AI 画像、导出建模结果。补充大文件识别性能优化、字段类型推断准确率提升和与外部表 external 的协作方式。",
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      "name": "人员数据接口",
      "description": "person-api",
      "prompt": "创建人员数据接口的 API 文档，覆盖人员基本信息、人员分组、亲密度、常住人口和数据画像等控制器。记录每个接口的 HTTP 方法、URL、请求参数、响应字段、分页格式和错误码。说明人员实体与通话、交易、轨迹、治理树等业务数据之间的关联查询方式，以及敏感字段的安全处理。提供查询某人员及其关系的 curl 示例，并说明人员不存在、分组为空、亲密度数据缺失等常见问题的排查方法。",
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      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/person/controller/PersonBasicInfoController.java,ai-server/src/main/java/com/zsjz/ai/module/person/controller/PersonGroupController.java,ai-server/src/main/java/com/zsjz/ai/module/person/controller/IntimacyController.java,ai-server/src/main/java/com/zsjz/ai/module/person/controller/ResidentPopulationController.java,ai-server/src/main/java/com/zsjz/ai/module/person/controller/DataProfileController.java",
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        "ai-server/src/main/java/com/zsjz/ai/module/person/controller/IntimacyController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/person/controller/ResidentPopulationController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/person/controller/DataProfileController.java"
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      "name": "构建、打包与自动更新",
      "description": "desktop-build-packaging-updater",
      "prompt": "为 Electron 桌面客户端的构建、打包与自动更新编写详细文档。说明 ai-electron/package.json 中的 scripts：dev、build、start、dev-frontend、dev-electron、build-frontend、build-electron、icon、build-w/m/l 等命令分别做什么，以及 ee-bin、electron-builder、vitest、electron-rebuild 的作用。解释 build 流程如何先构建前端，再构建 Electron 包，最后执行加密；说明 win64、win_e、mac_arm64、mac、linux 等平台构建目标的区别。说明 electron-updater 依赖如何参与客户端自动更新，以及 README.md 和 README.zh-CN.md 中关于安装、卸载、regInfo.exe、激活命令的使用说明。给出新增平台构建脚本、修改打包产物、接入更新服务器的示例。包含常见问题：前端构建失败、Electron 原生模块编译失败、图标缺失、安装包签名失败、自动更新服务器不可达等。",
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      "name": "后端服务架构",
      "description": "backend-service",
      "prompt": "编写后端服务架构文档，聚焦 ai-server 的 Spring Boot 应用组织方式。说明模块化原则：plat、agent、aiclean、knowledge、graph、person、call、trans、track、govern、search、dm、otg、external 等业务模块各自负责的领域对象、Controller/Service/Mapper 分层结构。解释多数据源配置（MyBatis-Plus + Dynamic Datasource）如何切换 PostgreSQL/DuckDB/pgvector；说明 Sa-Token 认证、SSE 心跳保活、定时任务与工作空间清理等横切能力。给出新增业务模块的标准模板：新建 module、定义 entity/mapper/service/controller，注册路由，并在数据库脚本中维护表结构。补充性能与可观测性建议。",
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      "name": "通话数据接口",
      "description": "call-data-api",
      "prompt": "创建通话数据接口的 API 文档，覆盖通话记录、夜间通话、连续通话和敏感通话控制器。记录每个接口的 HTTP 方法、URL、请求参数（如号码、时间范围、案件号）、响应字段、分页和排序方式。说明通话数据在调查场景中的用途，以及与人员、轨迹、治理树的关联关系。提供典型查询示例，并说明时间范围过大、号码为空、数据缺失等问题的排查方法。",
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      "kk_dependent_files": [
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        "ai-server/src/main/java/com/zsjz/ai/module/call/controller/CallNightController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/call/controller/CallContinuousController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/call/controller/CallSensitiveController.java"
      ]
    },
    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "时序与特殊日期模块 otg",
      "description": "business-otg",
      "prompt": "为时序与特殊日期模块 otg 创建详细文档。说明该模块管理时序数据、特殊日期配置和搜索控制器，为通话、交易、轨迹等业务提供时间维度的增强能力。解释什么是特殊日期（节假日、工作日、自定义事件日）以及它们如何影响行为分析和异常检测。梳理时序实体结构、时间粒度、特殊日期表、控制器路由和处理管道。给出示例：按工作日/节假日筛选通话或交易、标记特殊日期、结合时序趋势做异常报警。补充时序数据写入性能、时间索引优化和与其他模块共享时间上下文的最佳实践。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,sql/case_table.sql,sql/case_table_1.sql,sql/insight_agent_tables.sql",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "8f78a451-8218-40a1-9474-b29ba3fd8dca",
      "layer_level": 1,
      "order": 7,
      "kk_dependent_files": [
        "ai-server/pom.xml",
        "sql/case_table.sql",
        "sql/case_table_1.sql",
        "sql/insight_agent_tables.sql"
      ]
    },
    {
      "id": "4dfe4a9e-9c32-4f75-8314-3b06172b0d57",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "交易数据接口",
      "description": "trans-data-api",
      "prompt": "创建交易数据接口的 API 文档，覆盖资金流水、快速流水、固定存款、金融、现金、大额、频率、连续、卡持、敏感及对应 Key 配置等控制器。对每个接口说明 HTTP 方法、URL、请求参数、响应字段、分页、排序和错误码。说明交易数据与人员、账户、交易对手、治理树的关系，以及高频、大额、敏感交易在调查分析中的作用。提供按账户或人员查询交易的示例，并说明数据量大、时间范围过长、金额或时间格式错误等问题的排查方法。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransRecordController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFundFlowController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFastFundFlowController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFixedDepositController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFinancialController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransCashFlowController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransBigController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFrequencyController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransContinuousController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransCardHoldController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransSensitiveController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/FixedDepositKeyController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/FinancialKeyController.java,ai-server/src/main/java/com/zsjz/ai/module/trans/controller/CashKeyController.java",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "14469378-a6de-4dcb-907f-1edc16463b71",
      "layer_level": 1,
      "order": 8,
      "kk_dependent_files": [
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransRecordController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFundFlowController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFastFundFlowController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFixedDepositController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFinancialController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransCashFlowController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransBigController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransFrequencyController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransContinuousController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransCardHoldController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/TransSensitiveController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/FixedDepositKeyController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/FinancialKeyController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/trans/controller/CashKeyController.java"
      ]
    },
    {
      "id": "78886141-b043-4c17-a6c6-a2e7b67aea9a",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "外部表模块 external",
      "description": "business-external",
      "prompt": "为外部表模块 external 创建详细文档。说明该模块用于管理外部表、EntryRec 映射、协居、车辆违法、罪犯等第三方或外部来源数据，并与内部 person、call、trans、track 等实体打通。解释外部表的注册、字段映射、数据来源标识、权限控制和案件隔离机制。梳理 external_tables、external_table_field 等核心表结构，以及 EntryRec 映射如何把外部记录转换为内部可用对象。给出示例：新增外部数据源、配置字段映射、查询协居/车辆违法/罪犯信息、与内部人员匹配。补充外部数据同步策略、脏数据清洗、字段对齐和性能优化建议。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,sql/external_tables.sql,sql/external_table_field.sql,sql/case_table.sql,sql/case_table_1.sql",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "8f78a451-8218-40a1-9474-b29ba3fd8dca",
      "layer_level": 1,
      "order": 8,
      "kk_dependent_files": [
        "ai-server/pom.xml",
        "sql/external_tables.sql",
        "sql/external_table_field.sql",
        "sql/case_table.sql",
        "sql/case_table_1.sql"
      ]
    },
    {
      "id": "ec9a24fa-b5b6-4b28-96ab-06ee3089519f",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "Agent 与 RAG",
      "description": "agent-rag",
      "prompt": "为 Agent 与 RAG 功能创建详细文档。说明 Agent 对话的整体流程：前端发起 SSE 请求，后端通过 AgentScope 调用 LLM Provider（DashScope/Ollama/OpenAI），并结合 pgvector 做向量检索、Schema Catalog、意图识别、Python 执行器、附件上传、Artifact 管理和 Insight 输出。解释 Workspace Catalog、AgentMessage、AgentChatSession、RagIndexStatus 等关键数据模型之间的关系。给出典型调用示例：发送消息、选择模型、开启 RAG、查看工具调用结果。说明向量索引状态、嵌入调试接口和知识库集成。补充常见问题：SSE 断连、模型不可用、向量检索无结果、Python 执行器权限或超时等。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,ai-electron/frontend/src/ai/,ai-electron/frontend/src/call/,ai-electron/frontend/src/core/",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "order": 8,
      "kk_dependent_files": [
        "ai-server/pom.xml",
        "ai-electron/frontend/src/ai/",
        "ai-electron/frontend/src/call/",
        "ai-electron/frontend/src/core/"
      ]
    },
    {
      "id": "af886b13-8d59-4e6e-b5ea-40ddd68ef0a5",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "轨迹数据接口",
      "description": "track-data-api",
      "prompt": "创建轨迹数据接口的 API 文档，覆盖同行、同住、见面、同城、基站、快递信息等控制器。记录每个接口的 HTTP 方法、URL、请求参数、响应字段、分页和错误码。说明轨迹数据如何支持人员关联分析和时空调查，以及与人员、通话、交易、治理树的关系。提供按人员或时间范围查询轨迹的示例，并说明数据缺失、坐标无效、时间范围异常等问题的排查方法。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackTogetherTravelController.java,ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackTogetherLiveController.java,ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackMeetController.java,ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackEnLocalController.java,ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackCellTowerController.java,ai-server/src/main/java/com/zsjz/ai/module/track/controller/ExpressInfoController.java",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "14469378-a6de-4dcb-907f-1edc16463b71",
      "layer_level": 1,
      "order": 9,
      "kk_dependent_files": [
        "ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackTogetherTravelController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackTogetherLiveController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackMeetController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackEnLocalController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/track/controller/TrackCellTowerController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/track/controller/ExpressInfoController.java"
      ]
    },
    {
      "id": "fbd0f840-7bf0-40b1-9ae4-01dd991a8752",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "AI 数据清洗",
      "description": "ai-data-cleaning",
      "prompt": "编写 AI 数据清洗功能的详细文档。说明清洗模板、同义词、字段短名映射、批量清洗任务和清洗结果统计的数据模型与业务流程。解释 AiCleanTemplate、Synonym、FieldMapping、AiCleanRowStats 等实体之间的关系，以及清洗任务如何通过向量索引或规则匹配完成智能清洗。给出用户上传 CSV/Excel、匹配模板、执行清洗、查看结果和导出结果的完整示例。说明清洗任务的执行状态、错误日志和重试策略。补充常见问题：字段映射不准确、同义词未生效、批量任务卡住、向量索引缺失等。",
      "progress_status": "completed",
      "dependent_files": "sql/ai_clean.sql,sql/ai_clean_field_short_names.sql,sql/ai_clean_row_stats.sql,sql/ai_clean_synonym_init.sql,ai-electron/frontend/src/case/",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "order": 9,
      "kk_dependent_files": [
        "sql/ai_clean.sql",
        "sql/ai_clean_field_short_names.sql",
        "sql/ai_clean_row_stats.sql",
        "sql/ai_clean_synonym_init.sql",
        "ai-electron/frontend/src/case/"
      ]
    },
    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "治理与其他业务接口",
      "description": "govern-and-other-business-api",
      "prompt": "创建治理与其他业务接口的 API 文档，覆盖治理树、治理配置、搜索、时序、特殊日期和数据建模等控制器。记录各接口的 HTTP 方法、URL、请求参数、响应字段、分页和错误码。说明治理树在调查组织关系建模中的作用，搜索与时间序列在 otg 模块中的用途，以及 dm 数据建模接口如何辅助外部表和清洗流程。提供典型调用示例，并说明治理树结构异常、搜索结果为空、时序数据不完整、建模配置错误等问题的排查方法。",
      "progress_status": "completed",
      "dependent_files": "ai-server/src/main/java/com/zsjz/ai/module/govern/controller/GovernController.java,ai-server/src/main/java/com/zsjz/ai/module/govern/controller/GovernTreeController.java,ai-server/src/main/java/com/zsjz/ai/module/otg/controller/SearchController.java,ai-server/src/main/java/com/zsjz/ai/module/otg/controller/TimeSeriesController.java,ai-server/src/main/java/com/zsjz/ai/module/otg/controller/SpecialDateController.java,ai-server/src/main/java/com/zsjz/ai/module/dm/controller/DmController.java",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "parent_id": "14469378-a6de-4dcb-907f-1edc16463b71",
      "layer_level": 1,
      "order": 10,
      "kk_dependent_files": [
        "ai-server/src/main/java/com/zsjz/ai/module/govern/controller/GovernController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/govern/controller/GovernTreeController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/otg/controller/SearchController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/otg/controller/TimeSeriesController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/otg/controller/SpecialDateController.java",
        "ai-server/src/main/java/com/zsjz/ai/module/dm/controller/DmController.java"
      ]
    },
    {
      "id": "fde671b0-e5b4-4ff9-9baa-df07ebc75177",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "知识与向量检索",
      "description": "knowledge-vector-retrieval",
      "prompt": "创建知识与向量检索模块的文档。说明知识库、文档管理、向量库、下载日志和嵌入调试接口的设计与用法。解释文档如何被读取、向量化、存储到 pgvector，并在 Agent/RAG 检索中被召回。说明知识库与清洗模板、Agent Schema Catalog 的关系。给出上传文档、查看索引状态、调试 embedding、进行相似检索的示例。补充向量维度、索引刷新策略、文档去重、检索召回率调优和性能注意事项。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,ai-electron/frontend/src/ai/",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "order": 10,
      "kk_dependent_files": [
        "ai-server/pom.xml",
        "ai-electron/frontend/src/ai/"
      ]
    },
    {
      "id": "8f78a451-8218-40a1-9474-b29ba3fd8dca",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "业务数据模块",
      "description": "business-modules",
      "prompt": "汇总业务数据模块的总体文档，说明 person、call、trans、track、govern、search、dm、otg、external 等模块在调查场景中的职责和相互关系。解释这些模块如何围绕案件数据源、CaseDataSource、CaseInfo 和外部表组织数据，并通过 MyBatis-Plus 访问 PostgreSQL/pgvector/DuckDB。给出跨模块查询的典型场景：根据人员查通话、根据通话查交易、结合治理树和轨迹进行分析。说明数据建模 dm、外部表 external、时序 otg 和搜索 search 如何增强调查分析能力。补充性能优化建议和常见查询模式。",
      "progress_status": "completed",
      "dependent_files": "ai-server/pom.xml,sql/case_table.sql,sql/case_table_1.sql,sql/external_tables.sql,sql/table_data_1.sql,sql/insight_agent_tables.sql",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "order": 11,
      "kk_dependent_files": [
        "ai-server/pom.xml",
        "sql/case_table.sql",
        "sql/case_table_1.sql",
        "sql/external_tables.sql",
        "sql/table_data_1.sql",
        "sql/insight_agent_tables.sql"
      ]
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    {
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      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "数据库设计",
      "description": "database-design",
      "prompt": "创建完整的数据库设计文档。按业务域说明 PostgreSQL 主库表结构，包括 gateway_service/gateway_node、用户与授权、Agent 专家与工具、聊天附件、清洗模板与同义词、行统计、case_table、external_tables、insight_agent_tables、plat、user 等。说明 pgvector 向量表、DuckDB 临时数据源的用途和区别。给出 ER 关系图、关键字段定义、主外键、索引约束和业务规则。说明初始化脚本 sql/*.sql 的执行顺序、迁移规范和回滚注意事项。补充数据安全、访问控制和备份恢复建议。",
      "progress_status": "completed",
      "dependent_files": "sql/gateway.sql,sql/agent_expert.sql,sql/agent_tool.sql,sql/ai_clean.sql,sql/ai_clean_field_short_names.sql,sql/ai_clean_row_stats.sql,sql/ai_clean_synonym_init.sql,sql/case_table.sql,sql/case_table_1.sql,sql/chat_attachment.sql,sql/create_table_2.sql,sql/external_table_field.sql,sql/external_tables.sql,sql/insight_agent_tables.sql,sql/plat.sql,sql/table_data_1.sql,sql/user.sql",
      "gmt_create": "2026-10-28T07:55:29Z",
      "gmt_modified": "2026-10-28T07:55:29Z",
      "order": 12,
      "kk_dependent_files": [
        "sql/gateway.sql",
        "sql/agent_expert.sql",
        "sql/agent_tool.sql",
        "sql/ai_clean.sql",
        "sql/ai_clean_field_short_names.sql",
        "sql/ai_clean_row_stats.sql",
        "sql/ai_clean_synonym_init.sql",
        "sql/case_table.sql",
        "sql/case_table_1.sql",
        "sql/chat_attachment.sql",
        "sql/create_table_2.sql",
        "sql/external_table_field.sql",
        "sql/external_tables.sql",
        "sql/insight_agent_tables.sql",
        "sql/plat.sql",
        "sql/table_data_1.sql",
        "sql/user.sql"
      ]
    },
    {
      "id": "14469378-a6de-4dcb-907f-1edc16463b71",
      "repo_id": "afcc7ffe-ff4e-4271-8d3c-7a000d6d84ca",
      "name": "API 接口参考",
      "description": "api-reference",
      "prompt": "创建清鉴 AI 调查工具的 API 接口参考文档。按网关接口、系统基础 plat、Agent 对话、AI 清洗、知识检索、图谱、人员、通话、交易、轨迹、治理、外部表、数据建模等分组，说明 REST 接口的 HTTP 方法、URL 模式、请求参数、响应体结构和错误码。对于 Agent 对话，额外说明 SSE 连接建立、事件类型、消息格式和心跳保活协议。说明认证方式（x-token/Sa-Token）、跨域策略、分页、上传下载和速率限制。给出 curl 或前端调用示例，并说明常见错误（401、403、503、SSE 中断）的排查方法。",
      "progress_status": "completed",
      "dependent_files": "ai-gateway/src/main/java/com/zsjz/gateway/controller/AdminController.java,ai-server/src/main/java/com/zsjz/ai/",
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