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

1. 1. No hallucinations, ensuring stable and precise data extraction: Pre-configured workflows avoid AI-generated hallucinations.
2. No CAPTCHA issues: No need to handle reCAPTCHA or other verification challenges.
3. No IP restrictions or geo-blocking: No need to handle regional IP limitations.
4. Faster execution: Task execution is faster compared to pure AI-driven browser automation solutions.
5. 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:

1. 1. 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, INLINECODE4

1. 2. 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.

1. 3. publication_date (Publication Date Filter)

- Type: string - Description: Filter articles by their publication date. - Example: 3月11日, March 10, INLINECODE12

🚀 Invocation Method

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

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⏳ 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
• INLINECODE15: Article publication date
• INLINECODE16: Article author or publishing account name
• INLINECODE17: Main image URL or article cover image URL
• INLINECODE18: Full body content of the article
• INLINECODE19: 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:

1. 1. 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.

1. 2. 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

1. 1. Content Monitoring: Track mentions of specific brands or topics across WeChat articles.
2. Media Research: Analyze full text of articles published by top WeChat accounts.
3. Trend Tracking: Collect articles about rising industry trends (e.g., AI agents) for comprehensive reading.
4. Knowledge Base Building: Extract deep-dive articles into an internal repository.
5. Competitor Analysis: Review full-length posts released by competitor accounts.