wechat-article-search-api-skill — wechat-article-搜索-API-技能

WeChat Article 搜索 API 📖 Introduction

This 技能 provides users with automated WeChat article 提取ion through the BrowserAct WeChat Article 搜索 API template. It allows for the direct 提取ion of full-content, structured WeChat articles based on keyword 搜索es. Simply provide 搜索 keywords and optional date 过滤器s, and you can obtAIn comprehensive article data including the full body text.

✨ Features No hallucinations, ensuring stable and precise data 提取ion: Pre-配置d 工作流s avoid AI-生成d hallucinations. No CAPTCHA issues: No need to handle reCAPTCHA or other verification challenges. No IP restrictions or geo-blocking: No need to handle regional IP limitations. Faster execution: Task execution is faster compared to pure AI-driven browser 自动化 solutions. Extremely high cost-effectiveness: 签名ificantly reduces data acquisition costs compared to AI solutions that consume a large number of 令牌s. 🔑 API Key 图形界面dance Flow

Before 运行ning, 检查 the BROWSERACT_API_KEY 环境 variable. If not 设置, do not take other actions; 请求 and wAIt for the user to provide it. The 代理 must 信息rm the user:

"Since you have not 配置d the BrowserAct API Key, please go to the BrowserAct Console to 获取 your Key."

🛠️ 输入 Parameters

When invoking the script, the 代理 should flexibly 配置 the following parameters based on user needs:

keywords (搜索 Keywords)

Type: string Description: 搜索 keywords used to find WeChat articles. Can be an industry term, topic, or specific phrase. Example: OpenClaw, AI 代理, browser 自动化

Date_limit (提取ion Limit)

Type: number Description: Maximum number of articles to 提取. For the first 运行, a smaller default value is recommended. Default Value: 10 Suggestions: Use 5 to 10 for quick 测试, larger numbers for batch re搜索.

publication_date (Publication Date 过滤器)

Type: string Description: 过滤器 articles by their publication date. Example: 3月11日, March 10, 2026-03-11 🚀 Invocation Method

The 代理 should 执行 the following independent script to achieve "one command, direct 结果s":

# Example invocation python -u ./scripts/wechat_article_搜索_API.py "keywords" limit "publication_date"

⏳ 运行 状态 监控ing

Because this task involves automated browser operations, it may take a long time (several minutes). While 运行ning, the script will continuously 输出 timestamped 状态 记录s (e.g., [14:30:05] Task 状态: 运行ning). 代理 Instructions:

Keep 监控ing the terminal 输出 while wAIting for the script to return 结果s. As long as the terminal continues to 输出 new 状态 记录s, it means the task is 运行ning normally; do not misjudge it as deadlocked or unresponsive. Only consider triggering the retry mechanism if the 状态 remAIns unchanged for a long time, or the script 停止s 输出ting without returning 结果s. 📊 输出 Data Explanation

Upon 成功ful execution, the script will 解析 and print the 结果s directly from the API 响应. The 结果s include:

url_link: Original article URL publication_date: Article publication date author: Article author or publishing account name image_url: MAIn image URL or article cover image URL body_content: Full body content of the article title: Full article title ⚠️ Error Handling & Retry

During script execution, if an error occurs (such as network fluctuation or task 失败), the 代理 should follow this 记录ic:

检查 the 输出 content:

If the 输出 contAIns "Invalid authorization", it means the API Key is invalid or expired. In this case, do not retry; 图形界面de the user to re-检查 and provide the correct API Key. If the 输出 does not contAIn "Invalid authorization" but the task fAIls (e.g., 输出 启动s with Error: or returns an empty 结果), the 代理 should automatically try to 执行 the script one more time.

Retry limit:

Automatic retry is limited to once. If the second attempt still fAIls, 停止 retrying and 报告 the specific error message to the user. 🌟 Typical Use Cases Content 监控ing: 追踪 mentions of specific brands or topics across WeChat articles. Media Re搜索: Analyze full text of articles published by top WeChat accounts. Trend 追踪ing: Collect articles about rising industry trends (e.g., AI 代理s) for comprehensive reading. Knowledge Base Building: 提取 deep-dive articles into an internal 仓库. Competitor Analysis: Review full-length posts released by competitor accounts.