etl

What This Skill Does

The ETL (Extract-Transform-Load) skill for OpenClaw is a robust command-line toolkit designed for managing data pipelines with precision and transparency. Version 2.0.0 acts as a centralized record-keeping system for your data lifecycle activities. Instead of just performing transformations, the skill logs every critical step—ingestion, cleaning, validation, aggregation, and exporting—into structured, timestamped local text files. By providing a comprehensive audit trail, this skill ensures that your data engineering workflows are reproducible, observable, and easy to debug. Whether you are running complex SQL queries, defining schemas, or performing statistical profiling, the ETL skill keeps your activity history organized in the ~/.local/share/etl/ directory.

Installation

To integrate this skill into your OpenClaw agent, use the official installation command from the repository: clawhub install openclaw/skills/skills/bytesagain1/etl Ensure that you have appropriate write permissions for the ~/.local/share/ directory to allow the tool to initialize its logging system.

Use Cases

This skill is perfect for data engineers and analysts who need to maintain documentation for their data pipelines automatically. Use it when you are preparing datasets for machine learning models, cleaning messy CSV files, or performing routine data migrations. It is particularly useful when working on team-based projects where tracking schema changes or transformation logic is critical for version control. It also serves as a great tool for data health checks, using the etl profile and etl validate functions to catch anomalies before they reach production.

Example Prompts

1. "etl ingest 'source: customer_data.csv, rows: 5000, format: csv'" - Records the ingestion of a dataset.
2. "etl transform 'rename: user_id to customer_id, type_cast: date to ISO8601'" - Logs a specific data normalization step.
3. "etl validate 'check: null counts in email_column, result: passed'" - Documents the validation result of a data quality check.

Tips & Limitations

The ETL skill is a logging and management tool; it does not perform the heavy computation for the transformations themselves. You should run your data processing logic and then use the ETL commands to log what you have done. The tool is limited to local file storage, so it is highly performant but requires sufficient disk space for long-term logs. Use the etl stats and etl search commands frequently to keep your history clean and searchable. If your history grows too large, consider using the etl export command to move logs to long-term storage or analysis dashboards.