Hongguo Short Drama Market Weekly Report

Problem Background

In short drama content operations, rapid market insights are essential. Practitioners often need to answer questions like “What genres surged this week?” or “How did new dramas perform?”, but manually reviewing and compiling official weekly charts is time-consuming and error-prone. This skill addresses this by automating data fetching and analysis to generate structured reports.

Core Capabilities and Key Steps

The skill works with the official Hongguo short drama weekly chart API (base URL: https://fxb.chatvideoai.com), using the 热播指数 (a composite metric of play count, completion rate, etc.). It requires a Python 3 environment and relies solely on standard libraries like urllib and json, with no third-party dependencies. Key processes include:
- Issuing API requests based on user queries (defaulting to the latest week or specifying via the --week parameter) to fetch the TOP50 chart.
- Parsing JSON responses to extract fields such as drama name, genre, and 热播指数.
- Generating a Markdown report with nine sections: report header, core insights, TOP10 rankings, genre distribution, recent N-week trends, hot tags, tag combinations (e.g., “urban romance + face-slapping revenge”), new drama observations, and ranking changes.
- For deeper evaluation, the /v1/score endpoint can be called (via POST with parameters like genre and tags) to obtain topic scores, which can be integrated into the report.

Application Boundaries and Notes

• Data Accuracy: All figures come directly from API responses; fabricating drama names, ranks, or indices is strictly prohibited. The 热播指数 must be displayed as raw integers (e.g., 11627) without unit conversion.
• Error Handling: If API calls fail (e.g., due to network issues or status codes 503/404), the report should honestly state the error cause, avoiding the use of stale data.
• Customization: Users can adjust report content via parameters, such as specifying weeks or further evaluating new topics based on the report.
• Limitations: The skill focuses on official weekly chart analysis and is not suitable for historical deep dives or non-public data; it requires stable network connectivity, and data updates weekly.