WeChat Article Search API

📖 Introduction

This skill provides users with automated WeChat article extraction through the BrowserAct WeChat Article Search API template. It allows for the direct extraction of full-content, structured WeChat articles based on keyword searches. Simply provide search keywords and optional date filters, and you can obtain comprehensive article data including the full body text.

✨ Features

• No hallucinations, ensuring stable and precise data extraction: Pre-configured workflows avoid AI-generated 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 automation solutions.

• Extremely high cost-effectiveness: Significantly reduces data acquisition costs compared to AI solutions that consume a large number of tokens.

🔑 API Key Guidance Flow

Before running, check the BROWSERACT_API_KEY environment variable. If not set, do not take other actions; request and wait for the user to provide it.

The Agent must inform the user:

"Since you have not configured the BrowserAct API Key, please go to the BrowserAct Console to get your Key."

🛠️ Input Parameters

When invoking the script, the Agent should flexibly configure the following parameters based on user needs:

-

keywords (Search Keywords)

• Type: string

• Description: Search keywords used to find WeChat articles. Can be an industry term, topic, or specific phrase.

• Example: openclaw, AI agent, browser automation

-

Date_limit (Extraction Limit)

• Type: number

• Description: Maximum number of articles to extract. For the first run, a smaller default value is recommended.

• Default Value: 10

• Suggestions: Use 5 to 10 for quick testing, larger numbers for batch research.

-

publication_date (Publication Date Filter)

• Type: string

• Description: Filter articles by their publication date.

• Example: 3月11日, March 10, 2026-03-11

🚀 Invocation Method

The Agent should execute the following independent script to achieve "one command, direct results":

# Example invocation

python -u ./scripts/wechat_article_search_api.py "keywords" limit "publication_date"

⏳ Run Status Monitoring

Because this task involves automated browser operations, it may take a long time (several minutes). While running, the script will continuously output timestamped status logs (e.g., [14:30:05] Task Status: running).

Agent Instructions:

• Keep monitoring the terminal output while waiting for the script to return results.

• As long as the terminal continues to output new status logs, it means the task is running normally; do not misjudge it as deadlocked or unresponsive.

• Only consider triggering the retry mechanism if the status remains unchanged for a long time, or the script stops outputting without returning results.

📊 Output Data Explanation

Upon successful execution, the script will parse and print the results directly from the API response. The results 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 failure), the Agent should follow this logic:

-

Check the output content:

• If the output contains "Invalid authorization", it means the API Key is invalid or expired. In this case, do not retry; guide the user to re-check and provide the correct API Key.

• If the output does not contain "Invalid authorization" but the task fails (e.g., output starts with Error: or returns an empty result), the Agent should automatically try to execute the script one more time.

-

Retry limit:

• Automatic retry is limited to once. If the second attempt still fails, stop retrying and report the specific error message to the user.

🌟 Typical Use Cases

• Content Monitoring: Track mentions of specific brands or topics across WeChat articles.

• Media Research: Analyze full text of articles published by top WeChat accounts.

• Trend Tracking: Collect articles about rising industry trends (e.g., AI agents) for comprehensive reading.

• Knowledge Base Building: Extract deep-dive articles into an internal repository.

• Competitor Analysis: Review full-length posts released by competitor accounts.