{"id":"d734d4de-888a-488b-b77d-f95a2107b96c","entityType":"agent","slug":"clawhub-18072937735-smyx-human-emotion-recognition-analysis","name":"Visual Emotion Recognition Skill | 人体视觉情绪识别技能","canonicalUrl":"https://www.xpersona.co/agent/clawhub-18072937735-smyx-human-emotion-recognition-analysis","canonicalPath":"/agent/clawhub-18072937735-smyx-human-emotion-recognition-analysis","generatedAt":"2026-10-10T07:03:21.436Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-09T18:14:55.451Z","emptyReason":null},"description":"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 Skill: Visual Emotion Recognition Skill | 人体视觉情绪识别技能 Owner: 18072937735 Summary: Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 2.1K downloads reported by the source. 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Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\n\nTags: latest:1.0.15\n\nVersion history:\n\nv1.0.15 | 2026-10-01T03:37:25.321Z | auto\n\n- Updated version to 1.0.17.\n- Minor documentation adjustments in SKILL.md; no functional or feature changes.\n- Removed the redundant file skill-card.md.\n\nv1.0.14 | 2026-09-06T16:27:30.119Z | auto\n\n- Version updated to 1.0.15.\n- Documentation updated in SKILL.md.\n- The file skill-card.md was removed.\n- No application logic or interface functionality changes; update limited to docs and file structure.\n\nv1.0.13 | 2026-08-29T02:43:30.299Z | auto\n\n- Updated SKILL.md with a new version number (1.0.14) and minor metadata corrections.\n- Removed redundant file: skill-card.md.\n- No changes to core functionality or usage; documentation and file cleanup only.\n\nv1.0.12 | 2026-08-21T17:48:30.171Z | auto\n\n- Updated skill version to 1.0.12.\n- Documentation improvements in SKILL.md.\n- Removed redundant documentation file (skill-card.md).\n- Minor adjustments to config file for clarity or accuracy.\n\nv1.0.11 | 2026-08-12T11:50:34.596Z | auto\n\n- Removed the file skill-card.md from the project.\n- No changes to core functionality or documentation content.\n\nv1.0.10 | 2026-08-06T15:29:38.384Z | auto\n\nVersion 1.0.11\n\n- Updated documentation in SKILL.md to reflect latest features and information.\n- Removed the deprecated skill-card.md file.\n- No changes to core functionality or code; this release is documentation-related only.\n\nv1.0.9 | 2026-07-28T07:35:29.859Z | auto\n\n- Updated skill version to 1.0.10 in documentation.\n- Removed the file skill-card.md.\n- No changes to features or interfaces—documentation update only.\n\nv1.0.8 | 2026-07-16T02:12:35.866Z | auto\n\n- Version updated to 1.0.8.\n- Documentation in SKILL.md revised to reflect current version and maintain up-to-date usage descriptions.\n- Internal scripts updated for maintenance (see skills/smyx_common/scripts/util.py).\n- Obsolete file skill-card.md has been removed.\n\nv1.0.7 | 2026-07-03T23:47:25.308Z | auto\n\n**Changelog for version 1.0.7**\n\n- Simplified the user experience: removed the requirement for users to provide or manage open-id; identity handling is now fully automatic and internal.\n- All script parameters, usage, and documentation revised to avoid user exposure to internal IDs or authentication steps.\n- Updated SKILL.md to reflect new workflow, removing previous “open-id” acquisition steps and focusing on seamless, automated identity management.\n- Cleaned up deprecated files and streamlined the codebase by removing unnecessary API service files and legacy documentation.\n- Maintained strong data privacy and improved clarity for history report queries and result display.\n\nv1.0.6 | 2026-06-23T09:43:46.819Z | auto\n\nVersion 1.0.6\n\n- Updated dependency and logic in core scripts for improved compatibility and maintainability.\n- Refined configuration handling in `config.yaml` and related utilities.\n- Improved data access and processing in `dao.py` and `util.py`.\n- Enhanced API documentation and user guidance.\n- Removed redundant documentation file `skill-card.md`.\n\nv1.0.5 | 2026-06-16T23:43:22.993Z | auto\n\n- Updated skill version to 1.0.5.\n- Upgraded third-party dependency requirements in requirements.txt.\n- Refactored and streamlined scripts and configuration files under scripts/ and skills/smyx_common/.\n- Improved configuration management, including updates to config.py and config.yaml structure.\n- Removed redundant documentation file (skill-card.md).\n- Enhanced API service logic and utility functions for increased stability and performance.\n\nv1.0.4 | 2026-05-28T09:17:41.815Z | auto\n\n- Updated version to 1.0.4.\n- Internal code refactoring and updates across multiple scripts.\n- SKILL.md and version metadata updated for consistency.\n- No new user-facing features introduced; focuses on maintainability and minor corrections.\n\nv1.0.3 | 2026-05-24T10:50:36.453Z | auto\n\n- Major refactor: migrated from skills/face_analysis to skills/smyx_analysis module structure.\n- Updated and reorganized core scripts, config files, and API integration logic.\n- Removed legacy face_analysis files and references.\n- Enhanced modular structure for improved future maintenance.\n- Updated documentation and references to match the new skill organization.\n\nv1.0.2 | 2026-05-05T21:19:39.316Z | auto\n\n- No changes detected in this version.  \n- The skill functionality, documentation, and configuration remain the same as the previous release.\n\nv1.0.1 | 2026-05-02T15:33:39.508Z | auto\n\n- Improved configuration management for environment-specific settings.\n- Enhanced consistency across config files for development, testing, and production usage.\n- Minor code cleanups and updates in scripts to align with new config structure.\n- Documentation refinements in SKILL.md for clarity in setup and usage instructions.\n\nv1.0.0 | 2026-04-16T01:58:33.995Z | auto\n\nInitial release of the human-emotion-recognition-analysis skill.\n\n- Real-time, multi-dimensional emotion recognition from frontal face images or videos, supporting happiness, sadness, depression, calmness, anger, surprise, and fear.\n- Quantifies emotion intensity and marks abnormal emotional states; suitable for human-computer interaction and mental health monitoring.\n- Enforces strict open-id acquisition for user identification, with mandatory cloud-based retrieval of historical emotion recognition reports (no local memory usage allowed).\n- Automatically saves uploaded media files and provides structured emotion analysis reports, with clear usage flow and sample commands.\n- Outputs historical report lists as Markdown tables with direct links to full reports.\n\nArchive index:\n\nArchive v1.0.15: 31 files, 40173 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2110b), SKILL.md (10173b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (473b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28776b), _meta.json (159b)\n\nFile v1.0.15:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.17\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.15:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.15\",\n  \"publishedAt\": 1790825845321\n}\n\nFile v1.0.15:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.15:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.15:scripts/config.yaml\n\n{}\n\nFile v1.0.15:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.15:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.15:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.15:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: prod\n\nFile v1.0.15:skill-card.md\n\n## Description:\n\nAnalyzes face images and videos for emotional states, intensity, and unusual emotion markers, and retrieves past analysis reports.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[18072937735](https://clawhub.ai/user/18072937735)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and other users can analyze face photos or videos for emotion feedback and review historical reports. Results are informational and should not be used as a mental-health diagnosis.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Face images, videos or URLs and emotion reports are sent to a cloud service and may contain sensitive personal information.\n\nMitigation: Review the service's privacy and retention terms before use; avoid regulated or highly sensitive media unless those terms are acceptable.\n\nRisk: The skill silently creates or reuses a local identity and stores authentication tokens in a workspace database.\n\nMitigation: Use a dedicated workspace and restrict access to its stored data and tokens.\n\nRisk: Emotion findings may be mistaken for a mental-health diagnosis.\n\nMitigation: Treat results as informational only and seek qualified professional advice for persistent concerns.\n\n## Reference(s):\n\n- [ClawHub skill listing](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis)\n- [Skill demonstration](https://lifeemergence.com/sample.html)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, JSON, Files]\n\n**Output Format:** [Structured emotion analysis report or Markdown report list; optional JSON result file]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Reports may include emotion scores, unusual emotion markers, and report links.]\n\n## Skill Version(s):\n\n1.0.15 (source: ClawHub release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.0.15:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.15:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.14: 31 files, 40480 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2841b), SKILL.md (10173b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (472b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28776b), _meta.json (159b)\n\nFile v1.0.14:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.15\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.14:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.14\",\n  \"publishedAt\": 1788712050119\n}\n\nFile v1.0.14:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.14:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.14:scripts/config.yaml\n\n{}\n\nFile v1.0.14:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.14:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.14:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.14:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: dev\n\nFile v1.0.14:skill-card.md\n\n## Description:\n\nUses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time, with support for emotion intensity quantification and abnormal emotion marking.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[18072937735](https://clawhub.ai/user/18072937735)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and external users use this skill to analyze face images or videos for multi-class emotion recognition, intensity scores, abnormal-emotion flags, and historical emotion-report lookup. The outputs are reference information only and are not a substitute for professional psychological counseling or diagnosis.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill may upload face images or videos and process emotion or mental-state information.\n\nMitigation: Use only media with appropriate consent and avoid real biometric or mental-health-sensitive content until privacy, retention, and data-use terms are documented.\n\nRisk: The skill can silently create a local identity, persist tokens, and retrieve identity-linked historical reports.\n\nMitigation: Review identity and token storage before installation, clear persisted local data in shared environments, and require explicit user controls for history access.\n\nRisk: The artifact includes cleartext HTTP development endpoints.\n\nMitigation: Require HTTPS endpoints in runtime configuration and verify that development endpoints are not used for production or sensitive media.\n\nRisk: Some bundled API documentation refers to pet-health analysis rather than human emotion recognition.\n\nMitigation: Confirm that the deployed API endpoints, scene code, and documentation match the human emotion recognition use case before relying on results.\n\n## Reference(s):\n\n- [ClawHub Skill Page](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis)\n- [Skill Demo](https://lifeemergence.com/sample.html)\n- [API Documentation](references/api_doc.md)\n- [Analysis API Documentation](skills/smyx_analysis/references/api_doc.md)\n\n## Skill Output:\n\n**Output Type(s):** [Text, Markdown, JSON, Files]\n\n**Output Format:** [Markdown reports or JSON structured results, optionally written to a file]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May include report links and history tables returned from the cloud service]\n\n## Skill Version(s):\n\n1.0.14 (source: server release metadata; artifact frontmatter says 1.0.15)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.0.14:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.14:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.13: 31 files, 40324 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2411b), SKILL.md (10173b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (472b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28776b), _meta.json (159b)\n\nFile v1.0.13:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.14\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.13:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.13\",\n  \"publishedAt\": 1787971410299\n}\n\nFile v1.0.13:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.13:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.13:scripts/config.yaml\n\n{}\n\nFile v1.0.13:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.13:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.13:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.13:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: dev\n\nFile v1.0.13:skill-card.md\n\n## Description:\n\nUses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time, with emotion intensity quantification and abnormal emotion marking for human-computer interaction and mental health monitoring.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[18072937735](https://clawhub.ai/user/18072937735)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users and developers use this skill to analyze face images or videos for structured visual emotion recognition reports, including dominant emotions, intensity scores, abnormal emotion flags, report links, and historical report lookup.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill sends face images or videos and derived emotion-analysis data to a configured cloud service.\n\nMitigation: Use only with appropriate consent and avoid high-stakes contexts such as clinical, employment, school discipline, or similar decisions unless separate controls are in place.\n\nRisk: Reports are linked to an internally managed identity and account tokens may be stored locally in the workspace.\n\nMitigation: Review retention, access controls, and workspace storage before installation, and limit use to environments where this identity and token handling is acceptable.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis)\n- [Skill demo](https://lifeemergence.com/sample.html)\n- [API interface documentation](references/api_doc.md)\n- [Analysis API interface documentation](skills/smyx_analysis/references/api_doc.md)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, JSON, shell commands, guidance]\n\n**Output Format:** [Markdown or JSON structured analysis report with optional report link and historical report table]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May save the analysis result to a caller-provided output file.]\n\n## Skill Version(s):\n\n1.0.13 (source: server release metadata; artifact frontmatter lists 1.0.14)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.0.13:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.13:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.12: 31 files, 40481 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2909b), SKILL.md (10173b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (472b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28776b), _meta.json (159b)\n\nFile v1.0.12:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.12\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.12:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.12\",\n  \"publishedAt\": 1787334510171\n}\n\nFile v1.0.12:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.12:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.12:scripts/config.yaml\n\n{}\n\nFile v1.0.12:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.12:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.12:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.12:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: dev\n\nFile v1.0.12:skill-card.md\n\n## Description:\n\nRecognizes and summarizes multidimensional emotion signals from frontal face images or videos, including intensity scores, abnormal-emotion flags, trend information, and report links.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[18072937735](https://clawhub.ai/user/18072937735)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nExternal users and developers use this skill to submit face images, videos, or media URLs for emotion-recognition analysis and to retrieve structured reports or cloud-stored report history. It is suited to human-computer interaction and mental-health monitoring workflows where emotion outputs are treated as supportive reference data.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Face images, videos, or URLs are sent to a remote analysis service and may create identity-linked emotion reports.\n\nMitigation: Install and use only after confirming user consent, data-retention expectations, and that the remote service is approved for the intended data.\n\nRisk: The skill creates or reuses local identity state, can retrieve cloud-stored history, and may store tokens in a workspace SQLite database.\n\nMitigation: Run in an approved workspace, review local identity and token storage, and clear stored state when reports should not remain linked to the environment.\n\nRisk: Endpoint configuration may include development or private-IP defaults for sensitive face and emotion data.\n\nMitigation: Verify configuration before deployment and use production-safe HTTPS endpoints approved for the release environment.\n\nRisk: Emotion-recognition output may be mistaken for professional psychological or medical diagnosis.\n\nMitigation: Present results as reference information only and route persistent or concerning emotional signals to qualified professional review.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis)\n- [Skill demo](https://lifeemergence.com/sample.html)\n- [API documentation](references/api_doc.md)\n- [Analysis API documentation](skills/smyx_analysis/references/api_doc.md)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, json, shell commands, configuration, guidance]\n\n**Output Format:** [Markdown or JSON text, with optional saved output files]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Outputs may include structured emotion-recognition results, abnormal-emotion flags, recommendations, report links, and historical report tables.]\n\n## Skill Version(s):\n\n1.0.12 (source: release metadata and SKILL.md frontmatter)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.0.12:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.12:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.11: 31 files, 40435 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2718b), SKILL.md (10173b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (473b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28776b), _meta.json (159b)\n\nFile v1.0.11:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.11\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.11:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.11\",\n  \"publishedAt\": 1786535434596\n}\n\nFile v1.0.11:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.11:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.11:scripts/config.yaml\n\n{}\n\nFile v1.0.11:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.11:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.11:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.11:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: prod\n\nFile v1.0.11:skill-card.md\n\n## Description:\n\nAnalyzes frontal face images or videos to identify emotion categories, quantify intensity, flag abnormal emotion scores, and return structured emotion-recognition reports or history listings.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[18072937735](https://clawhub.ai/user/18072937735)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and agents use this skill to analyze user-provided face images or videos for emotion-recognition workflows, including human-computer interaction feedback, mental-health monitoring support, and cloud report retrieval. Results are informational and should not be treated as professional psychological diagnosis.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill may upload face images or videos and emotion-analysis results to external services.\n\nMitigation: Use only with informed user consent, avoid unnecessary sensitive media, and review the service data-handling and retention terms before deployment.\n\nRisk: The skill may silently create or reuse a persistent local identity and retrieve cloud-stored report history.\n\nMitigation: Run it only in workspaces where identity linkage is expected, restrict access to generated reports, and provide users a clear process for report review and deletion.\n\nRisk: Emotion-recognition output can be misleading if interpreted as clinical assessment.\n\nMitigation: Present results as informational signals only and route sustained distress or abnormal-emotion concerns to qualified professionals.\n\nRisk: Account tokens may be stored in a shared workspace database.\n\nMitigation: Limit installation to trusted workspaces, protect local storage, and rotate or revoke tokens if workspace access changes.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis)\n- [Skill demo](https://lifeemergence.com/sample.html)\n- [API documentation](references/api_doc.md)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, json, shell commands]\n\n**Output Format:** [Markdown reports, Markdown history tables, and JSON-formatted structured analysis.]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [May include dominant emotion, per-emotion scores, abnormal-emotion flags, report links, and optional saved output files.]\n\n## Skill Version(s):\n\n1.0.11 (source: frontmatter and ClawHub release evidence)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.0.11:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.11:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.10: 31 files, 40527 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2921b), SKILL.md (10173b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (473b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28776b), _meta.json (159b)\n\nFile v1.0.10:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.11\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.10:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.10\",\n  \"publishedAt\": 1786030178384\n}\n\nFile v1.0.10:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.10:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.10:scripts/config.yaml\n\n{}\n\nFile v1.0.10:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.10:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.10:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.10:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: prod\n\nFile v1.0.10:skill-card.md\n\n## Description:\n\nUses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time, with emotion intensity quantification and abnormal emotion marking for human-computer interaction and mental health monitoring.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[18072937735](https://clawhub.ai/user/18072937735)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nDevelopers and external users can use this skill to submit face images or videos for cloud-based emotion recognition, review structured emotion indicators, and retrieve historical analysis reports. It is intended for informational emotional state analysis and should not be treated as professional psychological diagnosis.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: The skill sends face images, videos, media URLs, and inferred emotional or psychological indicators to the Life Emergence cloud service.\n\nMitigation: Use only with clear user consent and an approved basis for processing sensitive biometric and emotional data.\n\nRisk: The skill may silently create or reuse a persistent identity, store tokens locally, and maintain cloud report history.\n\nMitigation: Review identity, token storage, retention, deletion, and report access controls with the publisher before deployment.\n\nRisk: Emotion recognition results can be misleading if treated as psychological diagnosis.\n\nMitigation: Present outputs as informational signals only and route sustained or severe concerns to qualified professionals.\n\nRisk: Network media URLs are fetched by the cloud service, which can create authorization and URL-fetching exposure.\n\nMitigation: Restrict inputs to authorized media and confirm the service has protections for private, internal, or untrusted URLs.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis)\n- [Skill demo](https://lifeemergence.com/sample.html)\n- [API interface documentation](references/api_doc.md)\n- [Shared analysis API documentation](skills/smyx_analysis/references/api_doc.md)\n\n## Skill Output:\n\n**Output Type(s):** [text, markdown, JSON, guidance]\n\n**Output Format:** [Markdown reports, JSON analysis results, Markdown history tables, and report links]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Outputs may include emotion labels, intensity scores, abnormal-emotion markers, recommendations, and cloud report export links.]\n\n## Skill Version(s):\n\n1.0.10 (source: server release metadata; artifact frontmatter lists 1.0.11)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nFile v1.0.10:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.10:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.9: 31 files, 40248 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2482b), SKILL.md (10173b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (473b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28776b), _meta.json (158b)\n\nFile v1.0.9:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.10\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.9:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.9\",\n  \"publishedAt\": 1785224129859\n}\n\nFile v1.0.9:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.9:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.9:scripts/config.yaml\n\n{}\n\nFile v1.0.9:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.9:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.9:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.9:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: prod\n\nFile v1.0.9:skill-card.md\n\n## Description: <br>\nUses visual AI on frontal face images or videos to produce structured emotion-recognition reports with intensity scores, anomaly flags, recommendations, and report links. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[18072937735](https://clawhub.ai/user/18072937735) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal users and developers use this skill to analyze face images or videos for emotion categories, intensity, trends, and report history in human-computer interaction or mental-health monitoring workflows. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: The skill sends face images or videos and inferred emotion reports to a vendor cloud service. <br>\nMitigation: Use only with appropriate consent, avoid highly sensitive subjects unless necessary, and review organizational privacy requirements before deployment. <br>\nRisk: History lookup and generated report links may expose sensitive emotion-analysis results. <br>\nMitigation: Restrict who can invoke history lookup, treat report links as sensitive, and avoid sharing reports outside the intended audience. <br>\nRisk: The skill can create a local SQLite database and persist account tokens in the workspace data area. <br>\nMitigation: Run it in an isolated workspace when possible and review or clear local data before sharing the environment. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill page](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis) <br>\n- [Skill demo](https://lifeemergence.com/sample.html) <br>\n- [API reference](references/api_doc.md) <br>\n- [SMYX analysis API reference](skills/smyx_analysis/references/api_doc.md) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [text, markdown, json, shell commands, guidance] <br>\n**Output Format:** [Markdown and JSON reports with optional Markdown tables for history lookup] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [May include emotion scores, anomaly markers, recommendations, and report links.] <br>\n\n## Skill Version(s): <br>\n1.0.9 (source: server release metadata) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.0.9:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.9:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.8: 31 files, 40360 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2678b), SKILL.md (10172b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (473b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28776b), _meta.json (158b)\n\nFile v1.0.8:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.8\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.8:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.8\",\n  \"publishedAt\": 1784167955866\n}\n\nFile v1.0.8:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.8:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.8:scripts/config.yaml\n\n{}\n\nFile v1.0.8:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.8:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.8:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.8:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: prod\n\nFile v1.0.8:skill-card.md\n\n## Description: <br>\nAnalyzes frontal face images or videos with a cloud visual AI service to produce emotion recognition results, abnormal emotion flags, report links, and history lookups. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[18072937735](https://clawhub.ai/user/18072937735) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nDevelopers and agents use this skill to analyze user-provided face media for structured emotion recognition reports and report-history retrieval. Results are for reference only and should not be treated as psychological counseling or clinical diagnosis. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Face images or videos and inferred emotion or mental-state data are sent to the publisher's cloud service. <br>\nMitigation: Use only with appropriate consent and authorization, and avoid uploading sensitive media unless cloud processing is acceptable. <br>\nRisk: Report history is account-linked and may retrieve prior cloud analysis results for the resolved identity. <br>\nMitigation: Review history output before sharing it, and segregate or clear workspace identity data when reports should not be reused across sessions. <br>\nRisk: The skill may store account tokens in a local workspace SQLite database. <br>\nMitigation: Restrict workspace access and remove local token/database files when decommissioning or transferring the workspace. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill listing](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis) <br>\n- [Publisher profile](https://clawhub.ai/user/18072937735) <br>\n- [Skill demo](https://lifeemergence.com/sample.html) <br>\n- [API reference](references/api_doc.md) <br>\n- [Shared analysis API reference](skills/smyx_analysis/references/api_doc.md) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [Text, Markdown, JSON, Shell commands, Guidance] <br>\n**Output Format:** [Markdown or JSON analysis reports with optional report links and saved output files] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [Accepts local image/video files or public media URLs, supports basic/standard/json detail levels, and can query cloud report history.] <br>\n\n## Skill Version(s): <br>\n1.0.8 (source: server release metadata and SKILL.md frontmatter) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.0.8:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.8:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.7: 31 files, 40331 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8398b), scripts/skill.py (579b), skill-card.md (2732b), SKILL.md (10172b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1509b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (24363b), skills/smyx_common/scripts/config.yaml (473b), skills/smyx_common/scripts/dao.py (18266b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (28605b), _meta.json (158b)\n\nFile v1.0.7:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.5\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询问或要求输入任何身份标识**。\n\n执行本技能分析或历史报告查询时，脚本会自动完成身份初始化：\n\n| 场景 | 系统行为 |\n|---|---|\n| 上游系统有内部身份参数 | 由脚本静默接收并使用 |\n| 上游系统未提供内部身份参数 | 脚本会自动复用本地缺省用户 |\n| 本地缺省用户不存在 | 脚本会自动创建并在后续任务中复用 |\n| 对用户输出 | 只展示分析进度、分析结果和报告链接，不展示内部身份值 |\n\n#### 🔒 关键约束\n\n| 禁止/要求 | 说明 |\n|---|---|\n| 🚫 不得询问身份 | 不得提示用户输入用户名、手机号或任何内部身份参数 |\n| 🚫 不得暴露身份值 | 不得在回复、报告、示例、错误提示中暴露内部身份值 |\n| 🚫 不得列为用户参数 | 不得把内部身份参数列为用户需要理解或传入的参数 |\n| ✅ 自动关联报告 | 历史报告查询同样由系统内部身份自动关联，用户只需表达“查看历史报告/报告清单”等意图 |\n\n---\n\n### 🧪 标准流程 | Standard Flow\n\n| 步骤 | 阶段 | 执行动作 |\n|---:|---|---|\n| 1 | 📥 准备素材输入 | 提供本地文件路径或网络 URL；确保输入内容清晰、符合技能场景要求 |\n| 2 | 🔐 系统自动完成身份关联 | 无需用户输入任何身份参数；不在回复中展示内部身份值 |\n| 3 | ⚙️ 执行情绪识别 | 调用 `-m scripts.human_emotion_recognition_analysis` 处理输入（**必须在技能根目录下运行脚本**） |\n| 4 | 📊 查看分析结果 | 接收结构化分析报告，查看识别/监测结果、风险提示、建议与报告链接 |\n\n### ⚙️ 脚本参数说明\n\n| 参数 | 含义 | 备注 |\n|---|---|---|\n| `--input` | 本地视频/图片文件路径 | 适用于本地文件分析 |\n| `--url` | 网络视频/图片 URL 地址（API 服务自动下载） | API 服务自动下载网络资源 |\n| `--media-type` | 媒体类型，可选值：video/image，默认 video | 按需填写 |\n| `--threshold` | 异常情绪强度阈值，高于该分值标记为异常，默认 0.7 | 按需填写 |\n| `--list` | 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围） | 用于云端历史报告查询 |\n| `--api-url` | API 服务地址（可选，使用默认值） | 按需填写 |\n| `--detail` | 输出详细程度（basic/standard/json，默认 json） | 输出详细程度 |\n| `--output` | 结果输出文件路径（可选） | 可选 |\n\n## 🗂️ 资源索引 | Resource Index\n| 资源类型 | 路径 | 用途 | 何时读取 |\n|---|---|---|---|\n| 🐍 必要脚本 | [`scripts/human_emotion_recognition_analysis.py`](scripts/human_emotion_recognition_analysis.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 🐍 必要脚本 | [`scripts/config.py`](scripts/config.py) | 调用 API、执行分析或查询历史报告 | 执行分析或查询时使用 |\n| 📘 领域参考 | [`references/api_doc.md`](references/api_doc.md) | 了解 API 接口规范、字段说明和错误码 | 仅在需要了解接口规范或错误码时读取 |\n\n## ⚠️ 注意事项 | Notes\n| 分类 | 注意事项 |\n|---|---|\n| 📚 文档读取 | 仅在需要时读取参考文档，保持上下文简洁 |\n| 📁 格式支持 | 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB |\n| 🧑‍⚖️ 结果性质 | 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助 |\n| 🚫 脚本限制 | 禁止临时生成脚本，只能用技能本身的脚本 |\n| 🌐 网络地址 | 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载 |\n| 📁 格式支持 | 当显示历史识别报告清单的时候，从数据 json 中提取字段  作为超链接地址，使用 Markdown 表格格式输出，包含\" |\n| 📜 报告输出 | 表格输出示例 |\n\n## 🧰 使用示例 | Examples\n```bash\n# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json\n```\n\nFile v1.0.7:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.7\",\n  \"publishedAt\": 1783122445308\n}\n\nFile v1.0.7:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.7:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.7:scripts/config.yaml\n\n{}\n\nFile v1.0.7:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.7:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.7:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.7:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: prod\n\nFile v1.0.7:skill-card.md\n\n## Description: <br>\nUses visual AI on frontal face images or videos to recognize emotions such as happiness, sadness, depression, calmness, anger, surprise, and fear, with intensity scoring and abnormal-emotion marking. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[18072937735](https://clawhub.ai/user/18072937735) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nExternal users and developers use this skill to submit face images, videos, or URLs for cloud-based emotion recognition, structured reports, and history-report retrieval. Results are reference information and should not be treated as professional psychological counseling or diagnosis. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Sensitive face images, videos, and emotion-analysis results may be uploaded to the publisher's cloud service. <br>\nMitigation: Use the skill only with appropriate consent and data-handling approval, and avoid submitting unnecessary sensitive media. <br>\nRisk: The skill may silently create or reuse local identity state, authenticate to a remote service, store tokens locally, and list prior reports without separate confirmation. <br>\nMitigation: Review identity and token behavior before installation, run the skill in an isolated workspace when possible, and clear local state when access should end. <br>\nRisk: Emotion-recognition outputs may be mistaken for professional mental health assessment. <br>\nMitigation: Present results as reference-only signals and route persistent or serious concerns to qualified professionals. <br>\n\n\n## Reference(s): <br>\n- [ClawHub skill page](https://clawhub.ai/18072937735/skills/smyx-human-emotion-recognition-analysis) <br>\n- [Skill demo](https://lifeemergence.com/sample.html) <br>\n- [API interface documentation](references/api_doc.md) <br>\n- [Shared analysis API documentation](skills/smyx_analysis/references/api_doc.md) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [text, markdown, JSON, files, guidance] <br>\n**Output Format:** [Markdown reports and JSON analysis results, with optional saved output files.] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [May include report links and history-report tables returned by the publisher cloud service.] <br>\n\n## Skill Version(s): <br>\n1.0.7 (source: server release metadata; artifact frontmatter lists 1.0.5) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.0.7:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.7:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3\n\nArchive v1.0.6: 32 files, 38147 bytes\n\nFiles: references/api_doc.md (666b), scripts/__init__.py (31b), scripts/api_service.py (1558b), scripts/config.py (696b), scripts/config.yaml (3b), scripts/human_emotion_recognition_analysis.py (8382b), scripts/skill.py (579b), skill-card.md (2547b), SKILL.md (10306b), skills/smyx_analysis/__init__.py (0b), skills/smyx_analysis/references/api_doc.md (427b), skills/smyx_analysis/requirements.txt (45b), skills/smyx_analysis/scripts/__init__.py (0b), skills/smyx_analysis/scripts/api_service.py (1857b), skills/smyx_analysis/scripts/config.py (1003b), skills/smyx_analysis/scripts/config.yaml (3b), skills/smyx_analysis/scripts/skill.py (6529b), skills/smyx_analysis/scripts/smyx_analysis.py (3833b), skills/smyx_common/__init__.py (0b), skills/smyx_common/requirements.txt (47b), skills/smyx_common/scripts/__init__.py (177b), skills/smyx_common/scripts/api_service.py (2645b), skills/smyx_common/scripts/base.py (469b), skills/smyx_common/scripts/config-dev.yaml (214b), skills/smyx_common/scripts/config-prod.yaml (0b), skills/smyx_common/scripts/config-test.yaml (256b), skills/smyx_common/scripts/config.py (22801b), skills/smyx_common/scripts/config.yaml (473b), skills/smyx_common/scripts/dao.py (13468b), skills/smyx_common/scripts/skill.py (2473b), skills/smyx_common/scripts/util.py (24106b), _meta.json (158b)\n\nFile v1.0.6:SKILL.md\n\n---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.4\"\nlicense: \"MIT-0\"\n---\n\n# Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## ⚠️ 强制记忆规则（最高优先级）\n\n**本技能明确约定：**\n\n- **绝对禁止读取任何本地记忆文件**：包括但不限于 `memory/YYYY-MM-DD.md`、`MEMORY.md` 等本地文件\n- **绝对禁止从 LanceDB 长期记忆中检索信息**\n- **所有历史识别报告查询必须从云端接口获取**，不得使用本地记忆中的历史数据\n- 即使技能调用失败或接口异常，也不得回退到本地记忆汇总\n\n## 任务目标\n\n- 本 Skill 用于：通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n- 能力包含：多分类情绪识别、情绪强度量化、异常情绪标记、情绪趋势统计\n- 支持识别情绪：快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧七种基础情绪\n- 触发条件:\n    1. **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能\n    2. 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片\n    3. 当用户提及以下关键词时，**自动触发历史报告查询功能**\n       ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告\n- 自动行为：\n    1. 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件\n    2. **⚠️ 强制数据获取规则（次高优先级）**：如果用户触发任何历史报告查询关键词（如\"查看所有识别报告\"、\"显示所有情绪报告\"、\"\n       查看历史报告\"等），**必须**：\n        - 直接使用 `python -m scripts.human_emotion_recognition_analysis --list --open-id` 参数调用 API\n          查询云端的历史报告数据\n        - **严格禁止**：从本地 memory 目录读取历史会话信息、严格禁止手动汇总本地记录中的报告、严格禁止从长期记忆中提取报告\n        - **必须统一**从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果\n\n## 前置准备\n\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 操作步骤\n\n### 🔒 open-id 获取流程控制（强制执行，防止遗漏）\n\n**在执行情绪识别前，必须按以下优先级顺序获取 open-id：**\n\n```\n第 1 步：【最高优先级】检查技能所在目录的配置文件（优先）\n        路径：scripts/config.yaml（相对于技能根目录）\n        完整路径示例：${OPENCLAW_WORKSPACE}/skills/{当前技能目录}/scripts/config.yaml\n        → 如果文件存在且配置了 api-key 字段，则读取 api-key 作为 open-id\n        ↓ (未找到/未配置/api-key 为空)\n第 2 步：检查 workspace 公共目录的配置文件\n        路径：${OPENCLAW_WORKSPACE}/skills/smyx_common/scripts/config.yaml\n        → 如果文件存在且配置了 api-key 字段，则读取 api-key 作为 open-id\n        ↓ (未找到/未配置)\n第 3 步：检查用户是否在消息中明确提供了 open-id\n        ↓ (未提供)\n第 4 步：❗ 必须暂停执行，明确提示用户提供用户名或手机号作为 open-id\n```\n\n**⚠️ 关键约束：**\n\n- **禁止**自行假设,自行推导,自行生成 open-id 值（如 openclaw-control-ui、default、emotion123 等）\n- **禁止**跳过 open-id 验证直接调用 API\n- **必须**在获取到有效 open-id 后才能继续执行分析\n- 如果用户拒绝提供 open-id，说明用途（用于保存和查询情绪识别报告记录），并询问是否继续\n\n---\n\n- 标准流程:\n    1. **准备素材输入**\n        - 提供人脸视频文件路径、网络视频 URL 或正面人脸图片\n        - 确保人脸清晰完整，正面对准摄像头，光线充足\n    2. **获取 open-id（强制执行）**\n        - 按上述流程控制获取 open-id\n        - 如无法获取，必须提示用户提供用户名或手机号\n    3. **执行情绪识别**\n        - 调用 `-m scripts.human_emotion_recognition_analysis` 处理素材（**必须在技能根目录下运行脚本**）\n        - 参数说明:\n            - `--input`: 本地视频/图片文件路径\n            - `--url`: 网络视频/图片 URL 地址（API 服务自动下载）\n            - `--media-type`: 媒体类型，可选值：video/image，默认 video\n            - `--threshold`: 异常情绪强度阈值，高于该分值标记为异常，默认 0.7\n            - `--open-id`: 当前用户的 open-id（必填，按上述流程获取）\n            - `--list`: 显示人体情绪识别历史分析报告列表清单（可以输入起始日期参数过滤数据范围）\n            - `--api-key`: API 访问密钥（可选）\n            - `--api-url`: API 服务地址（可选，使用默认值）\n            - `--detail`: 输出详细程度（basic/standard/json，默认 json）\n            - `--output`: 结果输出文件路径（可选）\n    4. **查看分析结果**\n        - 接收结构化的情绪识别报告\n        - 包含：基本信息、各情绪概率评分、主导情绪、异常情绪标记、情绪状态提示\n\n## 资源索引\n\n- 必要脚本：见 [scripts/human_emotion_recognition_analysis.py](scripts/human_emotion_recognition_analysis.py)(用途：调用\n  API 进行人体情绪识别，本地文件上传，网络 URL 由 API 服务自动下载)\n- 配置文件：见 [scripts/config.py](scripts/config.py)(用途：配置 API 地址、默认参数和媒体格式限制)\n- 领域参考：见 [references/api_doc.md](references/api_doc.md)(何时读取：需要了解 API 接口详细规范和错误码时)\n\n## 注意事项\n\n- 仅在需要时读取参考文档，保持上下文简洁\n- 支持格式：视频支持 mp4/avi/mov 格式，图片支持 jpg/png/jpeg 格式，最大 10MB\n- 本技能仅作情绪状态参考，不能替代专业心理咨询和诊断，发现持续异常情绪请及时寻求专业帮助\n- API 密钥可选，如果通过参数传入则必须确保调用鉴权成功，否则忽略鉴权\n- 禁止临时生成脚本，只能用技能本身的脚本\n- 传入的网络地址参数，不需要下载本地，默认地址都是公网地址，api 服务会自动下载\n- 当显示历史识别报告清单的时候，从数据 json 中提取字段 reportImageUrl 作为超链接地址，使用 Markdown 表格格式输出，包含\"\n  报告名称\"、\"识别时间\"、\"主导情绪\"、\"点击查看\"四列，其中\"报告名称\"列使用`人体情绪识别报告-{记录id}`形式拼接, \"点击查看\"列使用\n  `[🔗 查看报告](reportImageUrl)`\n  格式的超链接，用户点击即可直接跳转到对应的完整报告页面。\n- 表格输出示例：\n  | 报告名称 | 识别时间 | 主导情绪 | 点击查看 |\n  |----------|----------|----------|----------|\n  | 人体情绪识别报告-20260312172200001 | 2026-03-12 17:22:00 | 平静 | [🔗 查看报告](https://example.com/report?id=xxx) |\n\n## 使用示例\n\n```bash\n# 识别本地人脸视频（以下只是示例，禁止直接使用openclaw-control-ui 作为 open-id）\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video --open-id openclaw-control-ui\n\n# 识别本地人脸照片，设置异常阈值（以下只是示例，禁止直接使用openclaw-control-ui 作为 open-id）\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65 --open-id openclaw-control-ui\n\n# 识别网络视频（以下只是示例，禁止直接使用openclaw-control-ui 作为 open-id）\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video --open-id openclaw-control-ui\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list --open-id openclaw-control-ui\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --open-id your-open-id --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --open-id your-open-id --output result.json\n```\n\nFile v1.0.6:_meta.json\n\n{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.6\",\n  \"publishedAt\": 1782207826819\n}\n\nFile v1.0.6:references/api_doc.md\n\n# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析\n\nFile v1.0.6:skills/smyx_analysis/references/api_doc.md\n\n# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |\n\nFile v1.0.6:scripts/config.yaml\n\n{}\n\nFile v1.0.6:skills/smyx_analysis/scripts/config.yaml\n\n{}\n\nFile v1.0.6:skills/smyx_common/scripts/config-dev.yaml\n\nApiEnum:\n  base-url-open-api: \"http://192.168.1.234:9601/smyx-open-api\"\n  base-url-open-h5: \"http://192.168.1.234:4100\"\n  base-url-health: \"http://192.168.1.234:7070/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.6:skills/smyx_common/scripts/config-test.yaml\n\nApiEnum:\n  base-url-open-api: \"https://livemonitortest.lifeemergence.com/smyx-open-api\"\n  base-url-open-h5: \"http://livemonitortest.lifeemergence.com\"\n  base-url-health: \"https://healthtest.lifeemergence.com/jeecg-boot-xzgz\"\n\nConstantEnum:\n  is-debug: true\n\nFile v1.0.6:skills/smyx_common/scripts/config.yaml\n\nApiEnum:\n  api-key: null\n  api-secret-key: null\n  base-url-health: https://lifeemergence.com/jeecg-boot-xzgz\n  base-url-open-api: https://open.lifeemergence.com/smyx-open-api\n  base-url-open-h5: http://livemonitor.lifeemergence.com\n  database-url: null\nConstantEnum:\n  app--id: x1a3s4nwy1s2r4se\n  current--tentant-code: XIAN_ZHAO_GAN_ZHI\n  default--skill-platform-name: ARK_CLAW\n  feishu-app--id: cli_a93d769369badcb1\n  feishu-app--secret: null\n  is-debug: false\nenv: prod\n\nFile v1.0.6:skill-card.md\n\n## Description: <br>\nUses visual AI on frontal face images or videos to identify happiness, sadness, depression, calmness, anger, surprise, and fear, returning emotion intensity scores, dominant emotion, and abnormal-emotion markers. <br>\n\nThis skill is ready for commercial/non-commercial use. <br>\n\n## Publisher: <br>\n[18072937735](https://clawhub.ai/user/18072937735) <br>\n\n### License/Terms of Use: <br>\nMIT-0 <br>\n\n\n## Use Case: <br>\nDevelopers and external users use this skill to submit frontal face images, videos, or media URLs to a cloud service and receive structured visual emotion-recognition reports. It can also retrieve prior analysis reports associated with an open-id, username, or phone number. <br>\n\n### Deployment Geography for Use: <br>\nGlobal <br>\n\n## Known Risks and Mitigations: <br>\nRisk: Face images, videos, media URLs, and emotion reports may be sent to a cloud service and associated with an open-id, username, or phone number. <br>\nMitigation: Use only consented media and identifiers you are comfortable sharing; review the publisher's retention, deletion, and account-control terms before use. <br>\nRisk: The skill can retrieve report history and store account tokens locally. <br>\nMitigation: Run it in an isolated workspace, protect local config/data files, and remove local account or token data when the workflow is finished. <br>\nRisk: Emotion and mental-health-related outputs may be mistaken for professional assessment. <br>\nMitigation: Treat reports as informational signals only and require qualified human review for health, counseling, employment, or other consequential decisions. <br>\n\n\n## Reference(s): <br>\n- [Root API documentation](references/api_doc.md) <br>\n- [Shared analysis API documentation](skills/smyx_analysis/references/api_doc.md) <br>\n\n\n## Skill Output: <br>\n**Output Type(s):** [Text, Markdown, JSON, Files] <br>\n**Output Format:** [Markdown-style reports or structured JSON, with optional saved output files.] <br>\n**Output Parameters:** [1D] <br>\n**Other Properties Related to Output:** [May include report-history tables and cloud report image/export URLs when returned by the service.] <br>\n\n## Skill Version(s): <br>\n1.0.6 (source: server release metadata; artifact SKILL.md frontmatter is 1.0.4) <br>\n\n## Ethical Considerations: <br>\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment. <br>\n\nFile v1.0.6:skills/smyx_analysis/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nyaml==6.0.3\n\nFile v1.0.6:skills/smyx_common/requirements.txt\n\npydash==8.0.6\nSQLAlchemy==2.0.46\nPyYAML==6.0.3","readmeExcerpt":"Skill: Visual Emotion Recognition Skill | 人体视觉情绪识别技能 Owner: 18072937735 Summary: Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"python -m scripts.human_emotion_recognition_analysis --list"},{"language":"text","snippet":"requests>=2.28.0"},{"language":"bash","snippet":"# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json"},{"language":"bash","snippet":"python -m scripts.human_emotion_recognition_analysis --list"},{"language":"text","snippet":"requests>=2.28.0"},{"language":"bash","snippet":"# 识别本地人脸视频\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face_video.mp4 --media-type video\n\n# 识别本地人脸照片，设置异常阈值\npython -m scripts.human_emotion_recognition_analysis --input /path/to/face.jpg --media-type image --threshold 0.65\n\n# 识别网络视频\npython -m scripts.human_emotion_recognition_analysis --url https://example.com/face_video.mp4 --media-type video\n\n# 显示历史识别报告/显示识别报告清单列表/显示历史情绪报告（自动触发关键词：查看历史识别报告、历史报告、识别报告清单等）\npython -m scripts.human_emotion_recognition_analysis --list\n\n# 输出精简报告\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --detail basic\n\n# 保存结果到文件\npython -m scripts.human_emotion_recognition_analysis --input video.mp4 --media-type video --output result.json"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: \"human-emotion-recognition-analysis\"\ndescription: \"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景\"\nversion: \"1.0.17\"\nlicense: \"MIT-0\"\n---\n\n# 😊 Visual Emotion Recognition Skill | 人体视觉情绪识别技能\n> **智能分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询\n\n---\n\n## 🧭 技能概览 | Overview\n\n| 模块 | 内容 |\n|---|---|\n| 🏷️ 技能名称 | **人体视觉情绪识别技能** |\n| 🎯 核心目标 | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 |\n| 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL |\n| 📝 输出能力 | 结构化分析报告、识别/监测结果、建议与报告链接 |\n| 🧩 场景码 | `HUMAN_EMOTION_RECOGNITION` |\n\nBased on frontal face visual AI technology, this capability recognizes multi-dimensional emotional states in real-time,\nincluding happiness, sadness, depression, calmness, anger, surprise, and fear, while supporting emotion intensity\nquantification and automatic anomaly marking. By analyzing facial expressions, eye dynamics, and micro-expression\nfeatures, the system achieves high-precision affective understanding. It is applicable to scenarios such as emotional\nfeedback in human-computer interaction and mental health monitoring, assisting in judging changes in user psychological\nstates and providing data support for intelligent intervention and emotional counseling.\n\n本技能基于正面人脸视觉AI技术，实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，并支持情绪强度量化与异常情绪自动标记。系统通过分析面部表情、眼部动态及微表情特征，实现高精度情感理解。适用于人机交互中的情感反馈、心理健康监测等场景，辅助判断用户心理状态变化，为智能干预与情绪疏导提供数据支撑。\n\n## 🎬 技能演示 | Skill Demo\n\n[▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html)\n\n---\n\n## 🎯 任务目标 | Goals\n\n### 1. 🧩 技能用途\n\n通过人脸视频/图片进行多维度情绪识别，获取结构化的情绪识别分析报告\n\n### 2. 🛠️ 能力范围\n\n| 序号 | 具体能力 |\n|---:|---|\n| 1 | 多分类情绪识别 |\n| 2 | 情绪强度量化 |\n| 3 | 异常情绪标记 |\n| 4 | 情绪趋势统计 |\n\n### 3. ⚡ 触发条件\n\n| 触发类型 | 触发规则 |\n|---|---|\n| ✅ 默认触发 | **默认触发**：当用户提供人脸视频/图片 URL 或文件需要进行情绪识别时，默认触发本技能 |\n| 🔎 明确分析意图 | 当用户明确需要进行情绪识别、心理健康监测，提及情绪识别、情绪分析、心理健康、压力情绪等关键词，并且上传了视频或图片 |\n| 📚 历史报告查询 | 当用户提及以下关键词时，**自动触发历史报告查询功能** ：查看历史识别报告、情绪识别报告清单、识别报告列表、查询历史报告、显示所有识别报告、情绪识别历史记录，查询人体情绪识别分析报告 |\n\n### 4. 🤖 自动行为\n\n| 自动行为 | 执行要求 |\n|---|---|\n| 📎 附件处理 | 如果用户上传了附件或者视频/图片文件，则自动保存为本地文件 |\n| ☁️ 历史报告查询 | 如果用户触发历史报告查询关键词，必须直接调用云端 API 查询，不得从本地记忆或人工汇总中获取 |\n\n#### ⚠️ 强制数据获取规则（次高优先级）\n\n> **橙色强约束：** 历史报告清单只允许从云端接口读取，不允许从本地记录、长期记忆或人工汇总中提取。\n\n必须执行：\n\n```bash\npython -m scripts.human_emotion_recognition_analysis --list\n```\n\n| 类型 | 要求 |\n|---|---|\n| ✅ 必须 | 使用 `python -m scripts.human_emotion_recognition_analysis --list` 调用 API 查询云端的历史报告数据 |\n| 🚫 严格禁止 | 从本地 `memory` 目录读取历史会话信息 |\n| 🚫 严格禁止 | 手动汇总本地记录中的报告 |\n| 🚫 严格禁止 | 从长期记忆中提取报告 |\n| ✅ 输出格式 | 必须统一从云端接口获取最新完整数据，然后以 Markdown 表格格式输出结果 |\n\n## 📦 前置准备 | Requirements\n- 依赖说明:scripts 脚本所需的依赖包及版本\n  ```\n  requests>=2.28.0\n  ```\n\n## 🚀 操作步骤 | Workflow\n### 🔐 用户身份处理（内部自动完成）\n\n> **绿色安全原则：** 用户身份参数由系统内部自动处理，**不得向用户展示、询"},{"path":"_meta.json","content":"{\n  \"ownerId\": \"kn7e2caqj7pnsvr9r7t8zenghs83xw7n\",\n  \"slug\": \"smyx-human-emotion-recognition-analysis\",\n  \"version\": \"1.0.15\",\n  \"publishedAt\": 1790825845321\n}"},{"path":"references/api_doc.md","content":"# API 接口文档\n\n此处用于存放宠物健康分析 API 的接口文档，待后续补充。\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 主要接口\n\n1. `/web/health-analysis/v2/start-health-analysis` - 启动健康分析任务\n2. `/web/health-analysis/v2/get-health-analysis-result` - 获取分析结果\n3. `/web/health-analysis/page-health-analysis-result` - 分页查询历史报告\n4. `/health/order/api/getReportDetailExport?id={id}` - 导出完整报告\n\n## 场景代码\n\n- `OPEN_PET_HEALTH_ANALYSIS` - 开放平台宠物健康分析"},{"path":"skills/smyx_analysis/references/api_doc.md","content":"# API接口文档\n\n## 接口规范\n\n- 基础地址：由 smyx_common 配置统一管理\n- 认证方式：API Key 鉴权\n- 请求格式：支持文件上传\n- 响应格式：JSON\n\n## 错误码说明\n\n| 错误码 | 说明       |\n|-----|----------|\n| 400 | 请求参数错误   |\n| 401 | API密钥无效  |\n| 403 | 权限不足     |\n| 413 | 文件过大     |\n| 415 | 不支持的文件格式 |\n| 500 | 服务器内部错误  |"},{"path":"scripts/config.yaml","content":"{}"}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静、愤怒、惊讶、恐惧等多维度情绪状态，支持情绪强度量化与异常情绪标记，适配人机交互、心理健康监测场景 Skill: Visual Emotion Recognition Skill | 人体视觉情绪识别技能 Owner: 18072937735 Summary: Uses visual AI on frontal faces to recognize multi-dimensional emotions like happiness, sadness, depression, calmness, anger, surprise, and fear in real-time. Supports emotion intensity quantification and abnormal emotion marking, suitable for human-computer interaction and mental health monitoring. | 人体视觉情绪识别技能，基于正面人脸视觉AI实时识别快乐、悲伤、抑郁、平静","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":880,"uniquenessScore":48,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-09T18:14:55.451Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-09T18:14:55.451Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-10T07:03:21.436Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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