DataView

What This Skill Does

The DataView skill for OpenClaw is a powerful command-line data processing and logging toolkit designed to streamline the management of CSV and JSON datasets. It acts as an activity-focused data auditor, allowing users to ingest, transform, query, filter, aggregate, and visualize data while maintaining a robust, timestamped local audit trail. Every action performed through the DataView command suite is recorded as a pipe-delimited entry in dedicated log files located within your local directory, ensuring that your data manipulation workflow is fully reproducible and transparent. Whether you are performing quick ad-hoc data inspections or managing complex data pipelines, DataView provides the necessary structure to keep your research or development data organized.

Installation

To add the DataView skill to your OpenClaw agent, execute the following command in your terminal:

clawhub install openclaw/skills/skills/bytesagain1/dataview

Ensure that you have a standard Unix environment, as the skill relies on core utilities such as bash, sed, grep, and date. No external API keys or remote dependencies are required, making this a highly portable and private utility.

Use Cases

DataView is ideal for:

• Data Wrangling: Quickly filtering large log files or datasets to isolate relevant information.
• Audit Logging: Tracking every step of a data cleaning or transformation process for reporting purposes.
• Quick Summarization: Generating aggregate statistics or schemas on the fly without needing heavy database infrastructure.
• Pipeline Monitoring: Tracking the status and history of automated data pipelines through the dataview pipeline command.
• Local Analysis: Managing data locally on your machine while adhering to privacy-first workflows.

Example Prompts

1. "DataView, filter the sales.csv file to show only records where the region is 'North' and export the results to a new file."
2. "DataView, aggregate the customer data by status and show me the summary statistics."
3. "DataView, check the status of my data directory and show me the last 20 operations from the history logs."

Tips & Limitations

• Data Integrity: DataView uses a pipe-delimited storage format. Avoid using the pipe character | within your input values to ensure entries are parsed correctly.
• Performance: While excellent for CSV and JSON files, be aware that performance depends on your disk I/O speed. Very large datasets should be handled in chunks.
• Storage: The skill stores all data in ~/.local/share/dataview/. Periodically run dataview stats to monitor disk usage and ensure you don't run out of space due to extensive logging.
• Automation: Since it uses bash, you can easily pipe DataView output into other Unix tools like awk or jq for advanced processing.