csvglow converts tabular data into professional, interactive HTML dashboards with automated insights and visualizations.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install csvglow
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install csvglow using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
csvglow is a powerful utility designed to bridge the gap between raw data files and actionable insights. By processing CSV, TSV, or Excel files, it generates a single, self-contained HTML dashboard featuring a modern dark gradient theme. It does more than just plot data; it analyzes it, providing narrative insights that cross-reference metrics to help developers and analysts identify trends and anomalies without manual configuration. This makes it an essential tool for those using Openclaw Skills to streamline their data exploration workflows.
The tool is designed for portability and speed, requiring no server or CDN to function. Every generated dashboard is offline-ready and includes a comprehensive suite of analytical tools, from correlation heatmaps to time-series analysis, ensuring that your data tells a complete story immediately upon execution.
To start using this tool within your Openclaw Skills environment, ensure the binary is installed and run it against your data files.
# Generate a dashboard from a CSV and open it immediately
csvglow data.csv
# Process an Excel file and save it to a specific path
csvglow report.xlsx -o dashboard.html
# Run the tool without automatically opening the browser
csvglow data.csv --no-open
The skill organizes data into a structured HTML report with the following metadata taxonomy:
| Data Component | Description |
|---|---|
| Input Formats | Supports CSV, TSV, XLS, and XLSX file types |
| Statistics | Includes mean, median, standard deviation, quartiles, and missing value counts |
| Visualizations | Histograms, bar charts, categorical crosstabs, and time-series line charts |
| Advanced Analytics | Correlation heatmaps and auto-generated scatter plots for |
| Data Preview | A sortable, filterable table showing the first 1000 rows of the dataset |
| Portability | Self-contained HTML with no external dependencies (works offline) |
csvglow --mcp for seamless AI agent integration.Loading
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