小红书长图文发布 Skill
## 概述
About this skill
This AI agent skill provides robust sensitive content detection by leveraging the UCAP platform's advanced security API. It is designed to rapidly scan and identify various types of sensitive information within textual data, making it an essential tool for maintaining content integrity and regulatory compliance across diverse applications. The skill offers customizable detection types, allowing users to specify which categories of sensitive data should be flagged according to their specific needs. The skill outputs results in a standardized JSON format, which includes detailed detection findings from the UCAP interface and request parameters for debugging purposes. It incorporates comprehensive error handling and a 15-second timeout mechanism to ensure reliable and efficient operation. This makes it particularly suitable for integration into automated content review pipelines, enhancing the moderation of user-generated content, internal communications, or any textual information that requires careful scrutiny. Users would primarily utilize this skill to automate the often tedious and error-prone process of manual content moderation and compliance checks. By providing an AI agent with text, they can quickly obtain an objective assessment of its sensitivity, thereby preventing the publication of inappropriate or non-compliant material, reducing legal risks, and upholding platform standards more efficiently.
Best use case
The primary use case for this skill is automating content moderation and ensuring data compliance. It is invaluable for platforms, applications, or organizations that regularly handle large volumes of text and need to quickly identify and manage sensitive information to prevent violations. Content managers, legal compliance teams, and developers benefit significantly by using this skill to proactively flag problematic text, thereby minimizing reputational damage and legal liabilities while improving operational efficiency.
## 概述
Users should expect a JSON object detailing whether the provided text contains sensitive information, including the specific types and keywords detected by the UCAP platform API.
Practical example
Example input
请帮我检测这段文本是否包含敏感信息：这是一段包含敏感词汇的测试文本，例如“政治敏感”、“暴力倾向”以及虚构的身份证号123456789012345678。
Example output
{
"code": 0,
"message": "检测成功",
"data": {
"isSensitive": true,
"sensitiveKeywords": [
{"word": "政治敏感", "type": "POLITICAL_SENSITIVE"},
{"word": "暴力倾向", "type": "VIOLENCE_RELATED"},
{"word": "123456789012345678", "type": "ID_NUMBER"}
],
"detailedAnalysis": "..."
},
"request_params": {
"content": "这是一段包含敏感词汇的测试文本，例如“政治敏感”、“暴力倾向”以及虚构的身份证号123456789012345678。",
"userKey": "your_user_key_here",
"sensitive_code_list": []
}
}When to use this skill
- When moderating user-generated content on platforms or forums.
- For pre-publication checks of articles, marketing copy, or internal communications.
- To ensure compliance with data privacy regulations and content policies.
- When rapid, automated detection of sensitive keywords or phrases is required.
When not to use this skill
- If you do not have a valid UCAP platform userKey.
- For tasks unrelated to sensitive text detection.
- When handling extremely confidential data that cannot be sent to an external API.
- If your environment does not support Python 3.6+ or the `requests` library.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ctrip-flight-sunrise/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How 小红书长图文发布 Skill Compares
| Feature / Agent | 小红书长图文发布 Skill | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
## 概述
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 携程机票查询 Skill
## 概述
用于从携程网站搜索机票信息，获取地点、时间、价格、航班等结构化数据，支持比价分析、直飞/中转识别等功能。
## 技术实现
- **数据来源**: https://flights.ctrip.com
- **认证方式**: Cookie (FVP cookie from flights.ctrip.com)
- **数据提取**: 解析页面 JavaScript 中的 JSON 数据
- **支持功能**: 单程搜索、多日期比价
## 核心能力
1. **机票搜索** - 根据出发地、目的地、日期搜索航班
2. **数据提取** - 解析航班信息（航空公司、时刻、价格、机型等）
3. **结构化存储** - 输出 JSON 格式的航班数据
4. **比价分析** - 多日期、多航班价格对比
5. **低价监控** - 监控特定航线价格变化
## 搜索脚本使用
```bash
# 基本搜索
python3 scripts/ctrip_flight.py -d 北京 -a 上海 -t 2026-04-01
# 输出JSON文件
python3 scripts/ctrip_flight.py -d 北京 -a 上海 -t 2026-04-01 -o result.json
# 多日期比价
python3 scripts/ctrip_flight.py -d 北京 -a 上海 -t 2026-04-01 --compare 2026-04-01,2026-04-02,2026-04-03
```
## 搜索参数
| 参数 | 说明 | 示例 |
|------|------|------|
| -d, --departure | 出发城市 | 北京 |
| -a, --arrival | 到达城市 | 上海 |
| -t, --date | 出发日期 (YYYY-MM-DD) | 2026-04-01 |
| -c, --cabin | 舱位类型 (y/c/f) | y (经济舱) |
| -o, --output | 输出JSON文件路径 | result.json |
| --compare | 多日期对比，逗号分隔 | 2026-04-01,2026-04-02 |
## 输出格式
```json
{
"searchParams": {
"departure": "BJS",
"departureName": "北京",
"arrival": "SHA",
"arrivalName": "上海",
"date": "2026-04-01",
"cabin": "y"
},
"flights": [
{
"flightNo": "HO1254",
"airline": "吉祥航空",
"airlineCode": "HO",
"depTime": "2026-04-01 21:25:00",
"arrTime": "2026-04-01 23:35:00",
"duration": 130,
"depAirport": "大兴",
"depAirportCode": "PKX",
"arrAirport": "浦东",
"arrAirportCode": "PVG",
"planeType": "空客320",
"stops": 0,
"isDirect": true,
"price": 450
}
],
"statistics": {
"totalFlights": 11,
"directFlights": 11,
"transitFlights": 0,
"lowestPrice": 450,
"highestPrice": 550,
"avgPrice": 516
},
"searchTime": "2026-03-27T18:07:42"
}
```
## Cookie 配置
当前使用预设的 FVP cookie。如需更新：
1. 在 Chrome 中登录携程 flights.ctrip.com
2. 打开开发者工具 (F12) -> Application -> Cookies
3. 复制 FVP cookie 的值
4. 更新脚本中的 `self.cookie` 变量
## 已知限制
- Cookie 有时效性，可能需要定期更新
- 部分特殊航班数据可能不完整
- 经停航班的价格数据可能比直飞航班少
## 城市代码支持
支持中国主要城市：
北京(BJS), 上海(SHA), 广州(CAN), 深圳(SZX), 成都(CTU), 杭州(HGH), 南京(NKG), 武汉(WUH), 西安(XIY), 重庆(CKG), 厦门(XMN), 长沙(CSX), 昆明(KMG), 大连(DLC), 青岛(TAO), 天津(TSN), 郑州(CGO), 福州(FOC), 沈阳(SHE), 哈尔滨(HRB) 等
## 文件结构
```
skills/ctrip-flight/
├── skill.md # 本文档
├── README.md # 使用说明
└── scripts/
├── ctrip_flight.py # 主搜索脚本
└── ctrip_search.py # 备用搜索脚本
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