Jiangfeng

What This Skill Does

The Jiangfeng skill is a comprehensive data analysis engine designed specifically for e-commerce operators and financial analysts working within the ecosystem of 'Super Live' (超级直播) and 'Taobao Live' (淘宝直播). By leveraging the standard logic defined in the 'Data Analysis Foundation Concepts v3' document, this skill automates the ingestion, cleaning, and sophisticated calculation of advertising and financial metrics. It detects file encodings automatically, maps disparate datasets to standard business KPIs, and generates actionable, high-quality HTML and CSV reports. Whether it is calculating ROI, adjusting for refund rates across sales channels, or reconciling financial revenue against marketing spend, Jiangfeng transforms raw data exports into professional business intelligence.

Installation

To integrate this skill into your environment, use the ClawHub CLI tool. Ensure your Python environment meets the dependencies defined in requirements.txt (pandas >= 1.5.0, numpy >= 1.21.0, and chardet >= 5.0.0). Execute the following command in your terminal: clawhub install openclaw/skills/skills/18262202398-star/jiangfeng Once installed, you can configure the data processing range via environment variables or direct command-line arguments as detailed in the skill documentation.

Use Cases

This skill is highly effective for e-commerce managers and financial controllers. Common applications include:

• ROI Optimization: Calculating the return on investment for Super Live campaigns while filtering for actual realized revenue by incorporating refund rate adjustments.
• Performance Benchmarking: Analyzing unit costs such as 'viewing cost', 'order cost', and 'add-to-cart cost' to identify underperforming marketing channels.
• Financial Reconciliation: Normalizing business-side revenue against financial-side accounting standards to ensure tax and commission accuracy.
• Multi-dimensional Reporting: Merging financial, operational, and直播(Live) data to track the overall health of promotional campaigns.

Example Prompts

1. "Perform a data analysis for the period of 2026-01-01 to 2026-01-31. Use the data files located in the /data/january_report folder."
2. "Run the Jiangfeng analysis on my current directory files and calculate ROI, order cost, and conversion rates, saving the output in HTML format."
3. "Execute a cross-report analysis between my Super Live and financial exports, focusing on the promotion ROI metric, and generate a quality check report."

Tips & Limitations

To ensure optimal results, verify that your source files contain the required keywords ('超级直播', '淘宝直播', '财务') in their filenames so the auto-detection feature functions correctly. The skill is highly dependent on the structure of the input files; ensure they match the standard formats expected by your reporting pipeline. While the skill handles automatic encoding detection, highly corrupted files may require manual intervention. Always verify the data quality report generated alongside the analysis before making major budgetary decisions.