wechat-article-search-api-skill

## ✨ Features
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](https://www.browseract.com/reception/integrations) to get your Key."

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

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`, `browser automation`

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.

3. **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":

```bash
# 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:

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**.

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. **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.