Plant Nutrition Diagnosis Skill | 植物营养诊断技能
Diagnoses plant nutrient deficiency or excess based on computer vision and plant physiology, outputs targeted fertilization suggestions for precision nutrient management. | 植物营养诊断技能,基于计算机视觉与植物生理学,通过叶片特征诊断氮磷钾及微量元素缺乏或过剩,输出精准施肥建议 Skill: Plant Nutrition Diagnosis Skill | 植物营养诊断技能 Owner: smyx-sunjinhui Summary: Diagnoses plant nutrient deficiency or excess based on computer vision and plant physiology, outputs targeted fertilization suggestions for precision nutrient management. | 植物营养诊断技能,基于计算机视觉与植物生理学,通过叶片特征诊断氮磷钾及微量元素缺乏或过剩,输出精准施肥建议 Tags: latest:1.0.11 Version history: v1.0.11 | 2026-08-27T18:33:58.637Z | auto - Updated version number in SKILL
Rank
62
Safety
84
Downloads
1.8k
Updated
Oct 10, 2026
Version
1.0.11
Source
CLAWHUB
About
What it does, and when to use it.
Capability contract not published. No trust telemetry is available yet. 1.8K downloads reported by the source. Last updated 10/10/2026.
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 10, 2026
- Protocol compatibility
- OpenClawcompatibility · observed Oct 10, 2026
- Adoption signal
- 1.8K downloadsadoption · observed Oct 10, 2026
- Latest release
- 1.0.11release · observed Aug 27, 2026
- Handshake status
- UNKNOWNsecurity
Install and run
Setup complexity: low.
clawhub skill install s17cfv2h26b7hq5w47tgfy23xx83z9x6:smyx-plant-nutrition-diagnosis-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-smyx-sunjinhui-smyx-plant-nutrition-diagnosis-analysis/snapshot"
Documentation
CLAWHUB
125,622 characters of source documentation, loaded on request.
Extracted files
5 files captured from the source.
SKILL.md
--- name: "plant-nutrition-diagnosis-analysis" description: "Diagnoses plant nutrient deficiency or excess based on computer vision and plant physiology, outputs targeted fertilization suggestions for precision nutrient management. | 植物营养诊断技能,基于计算机视觉与植物生理学,通过叶片特征诊断氮磷钾及微量元素缺乏或过剩,输出精准施肥建议" version: "1.0.15" license: "MIT-0" --- # 🧪 Plant Nutrition Diagnosis Skill | 植物营养诊断技能 > **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 --- ## 🧭 技能概览 | Overview | 模块 | 内容 | |---|---| | 🏷️ 技能名称 | **植物营养诊断技能** | | 🎯 核心目标 | 植物营养诊断技能,基于计算机视觉与植物生理学,通过叶片特征诊断氮磷钾及微量元素缺乏或过剩,输出精准施肥建议 | | 🖼️ 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、识别/监测结果、建议与报告链接 | | 🧩 场景码 | `PLANT_SPECIES_RECOGNITION` | Based on computer vision technology combined with professional plant physiology knowledge, this skill accurately diagnoses nutrient imbalance disorders such as nitrogen, phosphorus, potassium deficiency or excess, as well as trace element abnormalities by analyzing the color, texture and morphological characteristics of plant leaves. The system quickly locates the type of nutrient imbalance based on "symptom location" (such as the difference between old leaves and new leaves) and "visual pattern" (such as interveinal chlorosis, leaf margin scorch), and outputs a structured diagnostic report including nutrient deficiency judgment, physiological cause analysis, and targeted fertilization suggestions. It provides scientific basis for precision fertilization and crop health management, helping growers quickly correct nutrient disorders and maintain healthy plant growth. 本技能结合计算机视觉技术与专业植物生理学知识,通过分析植物叶片的颜色、纹理和形态特征,能够精准诊断氮、磷、钾大量元素缺乏或过剩以及微量元素异常等营养失衡病症。系统依据" 症状发生部位"(如老叶与新叶的差异)及"视觉表现模式" (如叶脉间失绿、叶缘焦枯),快速定位营养失衡类型,输出包含缺乏元素判断、生理成因分析及针对性施肥建议的结构化诊断报告,为精准施肥与作物健康管理提供科学依据,帮助种植者快速矫正营养失调,维持植物健康生长。 ## 🎬 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 通过叶片视频/图片诊断植物营养状况,判断缺乏或过剩的营养元素,输出科学施肥建议 ### 2. 🛠️ 能力范围 | 序号 | 具体能力 | |---:|---| | 1 | 叶片特征提取 | | 2 | 营养元素缺乏/过剩诊断 | | 3 | 成因分析 | | 4 | 施肥建议输出 | ### 3. ⚡ 触发条件 | 触发类型 | 触发规则 | |---|---| | ✅ 默认触发 | **默认触发**:当用户提供植物叶片视频/图片需要诊断营养状况时,默认触发本技能 | | 🔎 明确分析意图 | 当用户明确需要植物营养诊断、缺肥判断时,提及叶子发黄、叶片失绿、缺氮缺磷、怎么施肥、营养诊断等关键词,并且上传了视频/图片,自动触发本技能 | | 📚 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** :查看历史诊断报告、营养诊断报告清单、诊断报告列表、查询历史诊断报告、显示所有诊断报告、植物营养分析报告,查询植物营养诊断分析报告 | ### 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.plant_nutrition_diagnosis_analysis --list ``` | 类型 | 要求 | |---|---| | ✅ 必须 | 使用 `python -m scripts.plant_nutrition_diagnosis_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 ``` ## 📸 诊断要求
_meta.json
{
"ownerId": "kn7cyxkr2ymf7zwsrybpedg8xx83ywrj",
"slug": "smyx-plant-nutrition-diagnosis-analysis",
"version": "1.0.11",
"publishedAt": 1787855638637
}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
{}skills/smyx_analysis/scripts/config.yaml
{}AionUi
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Machine-readable data
The same record, as JSON, for agents and crawlers.
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