powerdrill-data-analysis

What This Skill Does

The Powerdrill Data Analysis skill empowers users to bridge the gap between raw data files and actionable insights directly within the OpenClaw environment. By leveraging the Powerdrill REST API v2, this tool allows for the seamless management of datasets, automated ingestion of local files or public URLs, and the execution of complex natural-language analytical queries. Whether you are dealing with quarterly financial reports, marketing performance logs, or scientific datasets, this skill abstracts the technical complexity of data engineering. It enables users to list available datasets, check synchronization statuses, and generate high-level summaries and visualization questions, ensuring that data is always ready for exploration without requiring manual database management or complex SQL syntax.

Installation

To integrate this skill into your workflow, execute the following command in your terminal: clawhub install openclaw/skills/skills/javainthinking/powerdrill-skills

Before running your first analysis, ensure you have set up your environment variables: POWERDRILL_USER_ID and POWERDRILL_PROJECT_API_KEY. These keys authorize your agent to interact with your specific Powerdrill Teamspace. Additionally, ensure the requests library is installed via pip install requests and that the Python path in your configuration points to the location of powerdrill_client.py.

Use Cases

This skill is ideal for data-driven professionals, researchers, and developers. Use it to automate weekly sales reporting by uploading CSV files directly to a dataset. Researchers can use it to explore large datasets by running natural-language questions such as 'Identify the trends in the last quarter.' It is also perfect for identifying anomalies in log data or comparing performance metrics across different datasets stored in your Teamspace. By combining file-read operations with analytical querying, users can iterate on data insights rapidly.

Example Prompts

1. "Analyze the sales data in my 'Q4 Reports' dataset and tell me which region performed the best."
2. "I need to upload this local file to my current dataset and run an analysis to check for missing values."
3. "List all my existing datasets and provide a quick overview of the content in the 'Marketing Trends' project."

Tips & Limitations

Always verify dataset IDs before performing destructive operations like deletion. Since deleting a dataset is irreversible, the agent will prompt for confirmation. Note that data synchronization is asynchronous; use get_dataset_status if your recent uploads are not immediately returning insights. Ensure your data files are formatted cleanly before upload to minimize the number of 'invalid' data sources reported by the API. If you encounter authentication errors, double-check that your POWERDRILL_PROJECT_API_KEY has not expired.