Amazon Reviews Api Skill

## ✨ Features
1. **No Hallucinations**: Pre-set workflows avoid AI generative hallucinations, ensuring stable and precise data extraction.
2. **No Captcha Issues**: No need to handle reCAPTCHA or other verification challenges.
3. **No IP Restrictions**: No need to handle regional IP restrictions or geofencing.
4. **Faster Execution**: Tasks execute faster compared to pure AI-driven browser automation solutions.
5. **Cost-Effective**: Significantly lowers data acquisition costs compared to high-token-consuming AI solutions.

## 🔑 API Key Setup
Before running, check the `BROWSERACT_API_KEY` environment variable. If not set, do not take other measures; ask and wait for the user to provide it.
**Agent must inform the user**:
> "Since you haven't configured the BrowserAct API Key, please visit the [BrowserAct Console](https://www.browseract.com/reception/integrations) to get your Key."

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

1. **ASIN (Amazon Standard Identification Number)**
   - **Type**: `string`
   - **Description**: The unique identifier for the product on Amazon.
   - **Example**: `B07TS6R1SF`, `B08N5WRWJ6`

## 🚀 Usage
The Agent should execute the following independent script to achieve "one-line command result":

```bash
# Example call
python -u ./scripts/amazon_reviews_api.py "ASIN_HERE"
```

### ⏳ Execution Monitoring
Since this task involves automated browser operations, it may take some time (several minutes). The script will **continuously output status logs with timestamps** (e.g., `[14:30:05] Task Status: running`).
**Agent Instructions**:
- While waiting for the script result, keep monitoring the terminal output.
- As long as the terminal is outputting new status logs, the task is running normally; do not mistake it for a deadlock or unresponsiveness.
- Only if the status remains unchanged for a long time or the script stops outputting without returning a result should you consider triggering the retry mechanism.

## 📊 Data Output
After successful execution, the script will parse and print results directly from the API response. Each review item includes:
- `Commentator`: Reviewer's name
- `Commenter profile link`: Link to the reviewer's profile
- `Rating`: Star rating
- `reviewTitle`: Headline of the review
- `review Description`: Full text of the review
- `Published at`: Date the review was published
- `Country`: Reviewer's country
- `Variant`: Product variant info (if available)
- `Is Verified`: Whether it's a verified purchase

## ⚠️ Error Handling & Retry
If an error occurs during script execution (e.g., network fluctuations or task failure), the Agent should follow this logic:

1. **Check Output Content**:
   - If the output **contains** `"Invalid authorization"`, it means the API Key is invalid or expired. **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 failed (e.g., output starts with `Error:` or returns empty results), the Agent should **automatically try to re-execute the script once**.

2. **Retry Limit**:
   - Automatic retry is limited to **one time**. If the second attempt fails, stop retrying and report the specific error information to the user.

## 🌟 Typical Use Cases
1. **Competitor Analysis**: Extract reviews for competitors' products to understand their strengths and weaknesses.
2. **Product Feedback**: Summarize feedback for your own products to identify areas for improvement.
3. **Market Research**: Collect data on customer preferences and common complaints in a specific category.
4. **Sentiment Monitoring**: Monitor recent reviews to detect shifts in customer sentiment.
5. **QA Insights**: Use customer reviews to identify potential quality issues or bugs.
6. **Sentiment Analysis Prep**: Gather review text and ratings for detailed emotion modeling.
7. **Verified Purchase Analysis**: Compare feedback from verified vs. unverified buyers.
8. **Geographic Insights**: Analyze product performance across different reviewer countries.
9. **Variant Comparison**: Understand which product variants (size/color) receive the best feedback.
10. **Historical Trend Tracking**: Retrieve and analyze review publication dates to track product lifecycle sentiment.