A professional-grade data analysis toolkit for AI agents to query databases, automate spreadsheets, and generate visual insights.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install data-analyst
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install data-analyst using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Data Analyst?
The Data Analyst skill is a robust extension designed to provide AI agents with the capabilities of a junior data scientist. By leveraging this module within the ecosystem of Openclaw Skills, developers can enable their agents to interact directly with SQL databases, process complex Excel and CSV files using Pandas, and perform sophisticated statistical analysis. It is built to bridge the gap between raw data storage and actionable business intelligence, allowing for autonomous discovery of trends, correlations, and anomalies.
This skill goes beyond simple data retrieval; it provides a framework for data cleaning, quality auditing, and the generation of presentation-ready visualizations. Whether you are managing a local SQLite database or a cloud-based data warehouse like BigQuery, this skill ensures your AI agent can interpret data with context and precision.
Data Analyst Use Cases
- Automating the generation of weekly executive summaries and performance reports.
- Performing ad-hoc SQL queries for cohort and funnel analysis.
- Cleaning and standardizing inconsistent datasets from multiple source files.
- Creating visual trend charts and correlation heatmaps for marketing or sales data.
- Conducting statistical tests to validate business hypotheses and growth metrics.
How Data Analyst Works
- Configure the data source connections (SQL, Spreadsheets, or APIs) within the tools configuration file.
- Initialize the local analysis workspace and environment dependencies using the provided setup script.
- Input analytical questions or data processing requests to the AI agent.
- The agent executes cleaning protocols to handle nulls, duplicates, and outliers.
- Structured analysis is performed using optimized SQL patterns or Python-based data manipulation.
- Insights are synthesized into markdown reports, CSV exports, or visual image assets.
Data Analyst Setup
Configuration
First, define your data sources in your configuration file:
### Data Sources
- Primary DB: [Your Connection String]
- Spreadsheets: [URL or local path]
Workspace Initialization
Run the following command to prepare your environment:
./scripts/data-init.sh
Query Execution
You can run ad-hoc queries immediately using the CLI:
./scripts/query.sh "SELECT COUNT(*) FROM users"
Data Analyst Data Schema & Taxonomy
The Data Analyst skill utilizes a structured approach to manage data lineage and output quality.
| Component | Type | Description |
|---|---|---|
| Source Data | SQL/CSV/Excel | Input from relational databases or flat files. |
| Data Audit | Markdown | Checklists for nulls, duplicates, and formatting issues. |
| Processing | Pandas/SQL | Transformation logic and statistical aggregation. |
| Deliverables | Markdown/PNG/CSV | Final reports, charts, and cleaned datasets. |
Metadata such as source origins, last update timestamps, and applied filters are included in every generated report to ensure transparency.
Data Analyst Advanced Features
- Multi-source data joining across SQL databases and local spreadsheets.
- Advanced statistical toolkit support for T-tests, Chi-square, and ANOVA analysis.
- Automated cohort analysis and funnel conversion tracking templates.
- Dual-mode visualization: High-resolution PNG charts or terminal-friendly ASCII visualizations.
- Seamless integration with other Openclaw Skills for cross-departmental analytics like Marketing and Sales.
SKILL.md
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