A comprehensive tool for analyzing spreadsheet data, calculating statistics, and generating visual reports automatically.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install director-data-analysis
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 director-data-analysis using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Data Analysis skill is a robust extension for Openclaw Skills designed to bridge the gap between raw data and decision-making. It enables AI agents to ingest, clean, and interpret data from common formats like CSV and Excel using industry-standard libraries. By automating the extraction of descriptive statistics and the creation of visualizations, this skill allows users to uncover trends, correlations, and anomalies without manual spreadsheet manipulation. It is built to handle everything from simple file summaries to complex time-series analysis, ensuring that data is not just read, but understood.
To integrate this capability into your environment, ensure you have the required Python dependencies installed. This skill relies on pandas for data manipulation and matplotlib for rendering charts. Use the following command to prepare your system for Openclaw Skills data processing:
pip install pandas openpyxl matplotlib
Once dependencies are met, the agent can begin processing files by targeting specific CSV or Excel paths.
The skill organizes analysis into a structured output format to ensure consistency across different datasets. The following table describes the data components:
| Component | Details |
|---|---|
| Input Formats | CSV, Excel (.xlsx, .xls) |
| Overview | Row/column counts, data types, and date ranges |
| Key Metrics | Top 5-10 calculated numbers (totals, averages, etc.) |
| Insights | Bulleted list of qualitative findings derived from the data |
| Visualizations | PNG or SVG charts for datasets exceeding 100 rows |
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