Xpersona
agentCLAWHUBUnverified

Smart E-Bike Detection Skill | 电动车智能检测技能

Automatically detects electric motorcycles and e-bikes in restricted areas based on computer vision. It supports real-time detection for both video streams and images, counts the number of illegal parking or driving instances, and triggers violation alerts to assist with safety management in parks, communities, and organizations. | 电动车智能检测技能，基于计算机视觉自动检测禁行区域内的电动摩托车/电动车，支持视频流和图片实时检测，统计违规停放/行驶数量，触发违规预警，助力园区/社区/单位安全管理 Skill: Smart E-Bike Detection Skill | 电动车智能检测技能 Owner: 18072937735 Summary: Automatically detects electric motorcycles and e-bikes in restricted areas based on computer vision. It supports real-time detection for both video streams and images, counts the number of illegal parking or driving instances, and triggers violation alerts to assist with safety management in parks, communities, and organizations. | 电动车智能检测技能，

OpenClaw
View on ClawHubHomepage

Rank

62

Safety

84

Downloads

2.4k

Updated

Oct 9, 2026

Version

9.9.18

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 2.4K 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
2.4K downloadsadoption · observed Oct 9, 2026
Latest release
9.9.18release · observed Oct 1, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17f8q65zg3y98t86jdg1177g583whq8:smyx-electric-vehicle-detection-analysis
  1. 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.
  2. 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-electric-vehicle-detection-analysis/snapshot"

Documentation

CLAWHUB

152,761 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: "electric-vehicle-detection-analysis"
description: "Automatically detects electric motorcycles and e-bikes in restricted areas based on computer vision. It supports real-time detection for both video streams and images, counts the number of illegal parking or driving instances, and triggers violation alerts to assist with safety management in parks, communities, and organizations. | 电动车智能检测技能，基于计算机视觉自动检测禁行区域内的电动摩托车/电动车，支持视频流和图片实时检测，统计违规停放/行驶数量，触发违规预警，助力园区/社区/单位安全管理"
version: "1.0.20"
license: "MIT-0"
---

# ⚡ Smart E-Bike Detection Skill | 电动车智能检测技能

> **炫彩安全巡检中枢** · 视频/图片智能分析 · 违规电动车检测 · 园区/社区/单位安全管理

---

## 🧭 技能概览 | Overview

| 模块 | 内容 |
|---|---|
| 🏷️ 技能名称 | **Smart E-Bike Detection Skill / 电动车智能检测技能** |
| 🎯 核心目标 | 基于计算机视觉自动检测禁行区域内的电动摩托车/电动车 |
| 🖼️ 输入类型 | 监控视频流、静态图片、本地文件、网络媒体 URL |
| 🚨 输出能力 | 违规停放/行驶数量统计、违规等级预警、管理建议生成 |
| 🏢 适用场景 | 园区、社区、单位、校园、停车场、禁行道路等安全管理场景 |

Specifically designed for security management in industrial parks, communities, and institutions, this capability leverages computer vision technology to perform real-time analysis of video streams and static images. It automatically detects electric motorcycles and scooters entering restricted zones, accurately tallies the number of violations regarding illegal parking and driving, and promptly triggers alerts. This empowers management to efficiently control vehicle violations and significantly enhances the overall security management efficiency of the area.

该技能专为园区、社区及单位的安全管理场景打造，基于计算机视觉技术，可对视频流与静态图片进行实时分析，自动检测禁行区域内出现的电动摩托车或电动车，精准统计违规停放与行驶的数量，并及时触发违规预警，助力管理方高效管控车辆违规问题，提升区域安全管理效率。

---

## 🎬 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

本 Skill 用于：通过监控视频/图片进行电动车智能检测，自动识别禁行区域内的电动摩托车/电动车，统计车辆数量，触发违规预警，提升园区/社区/单位安全管理水平。

### 2. 🛠️ 能力范围

| 序号 | 具体能力 |
|---:|---|
| 1 | 支持监控视频与静态图片分析 |
| 2 | 电动车物体检测、电动摩托车识别 |
| 3 | 违规停放统计、违规行驶计数 |
| 4 | 违规等级预警 |
| 5 | 管理建议生成 |

### 3. ⚡ 触发条件

| 触发类型 | 触发规则 |
|---|---|
| ✅ 默认触发 | 当用户提供监控视频/图片 URL 或文件需要检测电动车时，默认触发本技能进行电动车检测分析 |
| 🔎 明确检测意图 | 当用户明确需要进行电动车检测、违规停车识别，提及电动车、电摩托车、禁行检测、违规停车、园区管理等关键词，并且上传了视频文件或者图片文件 |
| 📚 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**：查看历史检测报告、历史违规记录、电动车检测报告清单、查询历史报告、查看检测报告列表、显示所有检测报告、显示电动车分析报告，查询电动车检测分析报告 |

### 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 | 如果用户触发任何历史报告查询关键词（如“查看所有检测报告”、“显示所有违规记录”、“查看历史报告”等），必须直接调用云端 API 查询 |

#### ⚠️ 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.electric_vehicle_detection_analysis --list
```

| 类型 | 要求 |
|---|---|
| ✅ 必须 | 使用 `python -m scripts.electric_vehicle_detection_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：

```txt
requests>=2.28.0
```

---

## 🚀 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

_meta.json

{
  "ownerId": "kn7e2caqj7pnsvr9r7t8zenghs83xw7n",
  "slug": "smyx-electric-vehicle-detection-analysis",
  "version": "9.9.18",
  "publishedAt": 1790850144991
}

references/api_doc.md

# 电动车智能检测分析 API 文档

## 接口概述

本技能调用云端计算机视觉AI接口，自动识别禁行区域内的电动摩托车/电动车，统计车辆数量和违规情况，帮助园区、社区、单位进行违规停车/行驶管理，提升区域安全秩序。

## 支持检测车辆类型

| 车辆类型 | 描述 |
|----------|------|
| 电动摩托车 | 两轮电动摩托车 |
| 电动自行车 | 两轮电动自行车 |
| 电动轻便摩托车 | 轻便型电动车 |

## 支持禁行区域类型

| 区域类型 | 适用场景 |
|----------|----------|
| 停车场 | 禁停电动车停车场 |
| 社区园区 | 住宅小区、产业园区禁行区 |
| 校园单位 | 校园、机关单位禁行区 |
| 禁行道路 | 城市道路禁行电动车路段 |
| 其他 | 自定义禁行区域 |

## 违规等级划分

| 等级 | 描述 | 建议措施 |
|------|------|----------|
| 🟢 无违规 | 0辆电动车 | 无需处理 |
| 🟡 轻度违规 | 1-2辆电动车 | 记录提醒 |
| 🟠 中度违规 | 3-5辆电动车 | 需要清理 |
| 🔴 严重违规 | 5辆以上 | 立即清理整治 |

## API 响应字段说明

### 基础信息

| 字段 | 类型 | 说明 |
|------|------|------|
| id | string | 分析记录ID |
| data.analysis_time | string | 分析时间 |
| data.area_detection.status | string | 区域检测状态 |
| data.area_detection.quality_score | int | 画面质量评分 0-100 |

### 诊断结果

| 字段 | 类型 | 说明 |
|------|------|------|
| data.diagnosis.risk_score | int | 整体风险评分 0-100 |
| data.diagnosis.violation_level | string | 违规等级：normal/mild/moderate/severe |
| data.diagnosis.total_ev_count | int | 检测到电动车总量 |
| data.diagnosis.illegal_parking_count | int | 违规停放数量 |
| data.diagnosis.illegal_driving_count | int | 违规行驶数量 |
| data.diagnosis.average_density_per_frame | float | 平均每帧车辆密度 |
| data.diagnosis.vehicle_counts | object | 各类车辆计数 |
| data.diagnosis.violation_assessment | object | 违规程度评估 |

### 警示与建议

| 字段 | 类型 | 说明 |
|------|------|------|
| data.management_warnings | array[string] | 管理警示信息列表 |
| data.management_suggestions | array[string] | 处理建议列表 |

## 错误码说明

| 错误码 | 说明 |
|--------|------|
| 200 | 请求成功 |
| 400 | 请求参数错误 |
| 401 | API 鉴权失败 |
| 413 | 文件大小超出限制 |
| 415 | 不支持的文件格式 |
| 500 | 服务器内部错误 |
| 503 | 服务繁忙，请稍后重试 |

## 使用提示

1. 本工具仅辅助管理使用，最终违规认定需要人工复核
2. 监控视角对识别准确率影响较大，请确保摄像头覆盖完整禁行区域
3. 请遵守相关法律法规，保护个人隐私

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

{}

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Machine-readable data

The same record, as JSON, for agents and crawlers.

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Record generated Oct 10, 2026.

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