Bird Recognition Tool | 鸟类识别工具
Identifies bird species in images/videos of target areas. Supports recognition of no less than 500 common bird species, supports customized model training, suitable for ecological observation, garden bird watching and other scenarios. | 鸟类识别工具,识别目标区域图片/视频中的鸟类种类,支持不低于500种常见鸟类识别,支持定制化模型训练,适用于生态观测、庭院观鸟等场景 Skill: Bird Recognition Tool | 鸟类识别工具 Owner: 18072937735 Summary: Identifies bird species in images/videos of target areas. Supports recognition of no less than 500 common bird species, supports customized model training, suitable for ecological observation, garden bird watching and other scenarios. | 鸟类识别工具,识别目标区域图片/视频中的鸟类种类,支持不低于500种常见鸟类识别,支持定制化模型训练,适用于生态观测、庭院观鸟等场景 Tags: latest:1.0.22 Version history: v1.0.22 | 202
Rank
62
Safety
84
Downloads
2.3k
Updated
Oct 9, 2026
Version
1.0.22
Source
CLAWHUB
About
What it does, and when to use it.
Capability contract not published. No trust telemetry is available yet. 2.3K downloads reported by the source. Last updated 10/9/2026.
Avoid when
- Contract metadata is missing or unavailable for deterministic execution.
Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing
Public facts
Every fact links back to the source it came from.
- Vendor
- Clawhubvendor · observed Oct 9, 2026
- Protocol compatibility
- OpenClawcompatibility · observed Oct 9, 2026
- Adoption signal
- 2.3K downloadsadoption · observed Oct 9, 2026
- Latest release
- 1.0.22release · observed Sep 29, 2026
- Handshake status
- UNKNOWNsecurity
Install and run
Setup complexity: low.
clawhub skill install s17f8q65zg3y98t86jdg1177g583whq8:smyx-bird-recognition-analysis- Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
- Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.
Contract: missing
curl -s "https://www.xpersona.co/api/v1/agents/clawhub-18072937735-smyx-bird-recognition-analysis/snapshot"
Documentation
CLAWHUB
127,416 characters of source documentation, loaded on request.
Extracted files
5 files captured from the source.
SKILL.md
--- name: "bird-recognition-analysis" description: "Identifies bird species in images/videos of target areas. Supports recognition of no less than 500 common bird species, supports customized model training, suitable for ecological observation, garden bird watching and other scenarios. | 鸟类识别工具,识别目标区域图片/视频中的鸟类种类,支持不低于500种常见鸟类识别,支持定制化模型训练,适用于生态观测、庭院观鸟等场景" version: "1.0.17" license: "MIT-0" --- # 🐦 Bird Recognition Tool | 鸟类识别工具 > **智能健康/识别分析中枢** · 图片/视频智能分析 · 结构化报告 · 历史报告云端查询 --- ## 🧭 技能概览 | Overview | 模块 | 内容 | |---|---| | 🏷️ 技能名称 | **鸟类识别工具** | | 🎯 核心目标 | 鸟类识别工具,识别目标区域图片/视频中的鸟类种类,支持不低于500种常见鸟类识别,支持定制化模型训练,适用于生态观测、庭院观鸟等场景 | | 🖼️ 输入类型 | 图片、视频、本地文件、网络 URL | | 📝 输出能力 | 结构化分析报告、风险/识别结果、建议与报告链接 | | 🧩 场景码 | `BIRD_RECOGNITION` | This capability supports automatic bird identification in images or video streams, covering over 500 common species and capable of distinguishing between similar species and subspecies. Powered by deep learning visual models, the system can be deployed in ecological observation stations, nature reserves, or home backyards to enable real-time monitoring and recording of bird species. It also supports customized model training to optimize recognition performance based on specific regional or species requirements, providing intelligent assistance for bird diversity surveys, birdwatching hobbies, and ecological conservation. 本技能支持对图片或视频流中的鸟类进行自动识别,覆盖不低于500种常见鸟类,可区分相似种与亚种。系统基于深度学习视觉模型,可部署于生态观测站、自然保护区或家庭庭院等场景,实现鸟种实时监测与记录。同时支持定制化模型训练,根据特定区域或物种需求优化识别效果,为鸟类多样性调查、观鸟爱好及生态保护提供智能辅助。 ## 🎬 技能演示 | Skill Demo [▶️ 点击查看技能使用介绍](https://lifeemergence.com/sample.html) ## 🎯 任务目标 | Goals ### 1. 🧩 技能用途 识别图片/视频中出现的鸟类,准确判定鸟类品种 ### 2. 🛠️ 能力范围 | 序号 | 具体能力 | |---:|---| | 1 | 鸟类检测 | | 2 | 品种分类 | | 3 | 置信度评定 | ### 3. ⚡ 触发条件 | 触发类型 | 触发规则 | |---|---| | ✅ 默认触发 | **默认触发**:当用户提供图片/视频需要识别鸟类品种时,默认触发本技能 | | 🔎 明确分析意图 | 当用户明确需要鸟类识别、鸟种类鉴定时,提及观鸟、鸟类识别、鸟种类识别等关键词,并且上传了图片/视频 | | 📚 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、鸟类识别报告清单、识别报告列表、查询历史识别报告、显示所有识别报告、鸟类分析报告,查询鸟类识别分析报告 | ### 4. 🤖 自动行为 | 自动行为 | 执行要求 | |---|---| | 📎 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 | | ☁️ 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 | #### ⚠️ 强制数据获取规则(次高优先级) > **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。 必须执行: ```bash python -m scripts.bird_recognition_analysis --list ``` | 类型 | 要求 | |---|---| | ✅ 必须 | 使用 `python -m scripts.bird_recognition_analysis --list` 调用 API 查询云端的历史报告数据 | | 🚫 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 | | ✅ 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 | ## 📦 前置准备 | Requirements - 依赖说明:scripts 脚本所需的依赖包及版本 ``` requests>=2.28.0 ``` ## 📸 识别要求 | Recognition Requirements | 要求项 | 说明 | |---|---| | 要求 | 如果是视频,建议截取鸟类清晰停留的片段上传 | ## 🚀 操作步骤 | Workflow ### 🔐 用户身份处理(内部自动完成) > **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**。 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: | 场景 | 系统行为 | |---|---| | 上游系统有内部身份参数 | 由脚本静默接收并使用 | | 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 | | 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 |
_meta.json
{
"ownerId": "kn7e2caqj7pnsvr9r7t8zenghs83xw7n",
"slug": "smyx-bird-recognition-analysis",
"version": "1.0.22",
"publishedAt": 1790666852214
}references/api_doc.md
# API 接口文档
此处用于存放鸟类识别分析 API 的接口文档,待后续补充。
## 接口规范
- 基础地址:由 smyx_common 配置统一管理
- 认证方式:API Key 鉴权
- 请求格式:支持文件上传
- 响应格式:JSON
## 主要接口
1. `/web/ai-analysis/v2/start-common-ai-analysis` - 启动AI分析任务
2. `/web/ai-analysis/v2/get-common-ai-analysis-result` - 获取分析结果
3. `/web/ai-analysis/page-common-ai-analysis-result` - 分页查询历史报告
4. `/ai/order/api/getReportDetailExport?id={id}` - 导出完整报告
## 场景代码
- `OPEN_BIRD_RECOGNITION_ANALYSIS` - 开放平台鸟类识别分析skills/smyx_analysis/references/api_doc.md
# API接口文档 ## 接口规范 - 基础地址:由 smyx_common 配置统一管理 - 认证方式:API Key 鉴权 - 请求格式:支持文件上传 - 响应格式:JSON ## 错误码说明 | 错误码 | 说明 | |-----|----------| | 400 | 请求参数错误 | | 401 | API密钥无效 | | 403 | 权限不足 | | 413 | 文件过大 | | 415 | 不支持的文件格式 | | 500 | 服务器内部错误 |
scripts/config.yaml
{}AionUi
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Machine-readable data
The same record, as JSON, for agents and crawlers.
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