agentCLAWHUBUnverified

Fire & Smoke Detection Skill | 火情烟雾检测技能

Real-time detection of flames and smoke in video and image scenes. Suitable for fire early warning in industrial parks, forests, warehouses, and other locations. | 火情烟雾检测技能,实时检测视频/图片场景中的火焰、烟雾,适用于工业园区、森林、仓库等场所火情预警 Skill: Fire & Smoke Detection Skill | 火情烟雾检测技能 Owner: 18072937735 Summary: Real-time detection of flames and smoke in video and image scenes. Suitable for fire early warning in industrial parks, forests, warehouses, and other locations. | 火情烟雾检测技能,实时检测视频/图片场景中的火焰、烟雾,适用于工业园区、森林、仓库等场所火情预警 Tags: latest:1.0.22 Version history: v1.0.22 | 2026-10-03T03:43:40.233Z | auto - Removed the documentation file skill-card.md. - No

OpenClaw

Rank

62

Safety

84

Downloads

2.1k

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. 2.1K 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
2.1K downloadsadoption · observed Oct 9, 2026
Latest release
1.0.22release · observed Oct 3, 2026
Handshake status
UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17f8q65zg3y98t86jdg1177g583whq8:smyx-fire-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-fire-detection-analysis/snapshot"

Documentation

CLAWHUB

121,856 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: "fire-detection-analysis"
description: "Real-time detection of flames and smoke in video and image scenes. Suitable for fire early warning in industrial parks, forests, warehouses, and other locations. | 火情烟雾检测技能,实时检测视频/图片场景中的火焰、烟雾,适用于工业园区、森林、仓库等场所火情预警"
license: "MIT-0"
---

This capability supports real-time detection of flames and smoke in video streams or images, making it suitable for high
fire-risk locations such as industrial parks, forests, and warehouses. Based on color features, dynamic texture
analysis, and smoke diffusion models, the system can rapidly identify early-stage fire conditions while filtering out
interferences like lighting changes and steam. Once an anomaly is detected, it immediately triggers local audio-visual
alarms and pushes remote warning messages, facilitating second-level discovery and rapid response to fire incidents,
effectively reducing the risk of fire spread.

本技能支持对视频流或图片中的火焰、烟雾进行实时检测,适用于工业园区、森林、仓库等高火险场所。系统基于颜色特征、动态纹理与烟雾扩散模型,能够快速识别早期火情并排除光照、蒸汽等干扰。一旦检测到异常,立即触发本地声光报警并远程推送预警信息,助力实现火情的秒级发现与快速处置,有效降低火灾蔓延风险。

# 🔥 Fire & Smoke Detection Skill | 火情烟雾检测技能
> **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 | **火情烟雾检测技能** |
| 🎯 核心目标 | 火情烟雾检测技能,实时检测视频/图片场景中的火焰、烟雾,适用于工业园区、森林、仓库等场所火情预警 |
| 🖼️ 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 | `FIRE_DETECTION` |

## 🎬 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

检测图片/视频场景中的火情,识别火焰和烟雾,及时发出预警

### 2. 🛠️ 能力范围

| 序号 | 具体能力 |
|---:|---|
| 1 | 火焰检测 |
| 2 | 烟雾识别 |
| 3 | 位置标定 |
| 4 | 置信度评估 |
| 5 | 火情等级判断 |

### 3. ⚡ 触发条件

| 触发类型 | 触发规则 |
|---|---|
| ✅ 默认触发 | **默认触发**:当用户提供监控视频/图片需要检测火情烟雾时,默认触发本技能 |
| 🔎 明确分析意图 | 当用户明确需要火情检测、火灾预警时,提及火焰检测、烟雾识别、火情预警、火灾检测等关键词,并且上传了视频/图片 |
| 📚 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、火情检测报告清单、检测报告列表、查询历史检测报告、显示所有检测报告、火情分析报告,查询火情检测分析报告 |

### 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.fire_detection_analysis --list
```

| 类型 | 要求 |
|---|---|
| ✅ 必须 | 使用 `python -m scripts.fire_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
  ```
  requests>=2.28.0
  ```

## 📸 检测要求 | Detection Requirements
| 要求项 | 说明 |
|---|---|
| 监控画面清晰 | ,尽量覆盖容易起火的重点区域 |
| 避免大面积遮挡 | ,保证疑似火源区域完整可见 |
| 支持白天和夜间红外监控,确保人形/火源轮廓可见 | 支持白天和夜间红外监控,确保人形/火源轮廓可见 |

## 🚀 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 |
| 对用户输出

_meta.json

{
  "ownerId": "kn7e2caqj7pnsvr9r7t8zenghs83xw7n",
  "slug": "smyx-fire-detection-analysis",
  "version": "1.0.22",
  "publishedAt": 1790999020233
}

references/api_doc.md

# API 接口文档

此处用于存放火情烟雾检测分析 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_FIRE_DETECTION_ANALYSIS` - 开放平台火情检测分析

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

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Machine-readable data

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

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Record generated Oct 9, 2026.

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