ChartGen AI is a comprehensive visualization and data analysis skill that transforms raw data into professional charts, dashboards, and PowerPoint reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install chartgen-ai
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 chartgen-ai 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 ChartGen AI?
ChartGen AI is a specialized skill designed for Openclaw Skills that bridges the gap between raw datasets and actionable visual insights. It leverages a robust API to handle complex tasks ranging from simple trend line generation to advanced multi-file data joins and outlier detection. Whether you are dealing with a single CSV or a collection of Excel spreadsheets, this skill provides a structured way for AI agents to analyze data and produce high-quality outputs.
The skill is built to be user-centric, ensuring that no processing happens without explicit human confirmation. It supports a wide array of visual formats including ECharts, Mermaid diagrams, and full PowerPoint presentations, making it an essential tool for developers and analysts who need to automate reporting workflows within their AI agent environment.
ChartGen AI Use Cases
- Generating complex data visualizations like Heatmaps, Treemaps, and Waterfall charts from uploaded spreadsheets.
- Automating the creation of business dashboards and Gantt charts for project management.
- Performing deep data analysis to identify year-over-year (YoY) trends and statistical anomalies.
- Creating professional PowerPoint (PPTX) presentations complete with analysis findings and preview images.
- Visualizing technical architecture through Flowcharts, Sequence diagrams, and ER diagrams.
How ChartGen AI Works
- Confirmation Phase: The skill identifies user intent or file uploads and presents a numbered list of proposed analysis tasks (Go, Modify, or Cancel).
- Submission: Upon user approval, the skill notifies the user of the expected processing time and executes the submit command via the ChartGen API.
- Asynchronous Processing: The skill handles the processing time (up to 25 minutes for PPTs) using background execution or periodic polling to monitor the task status.
- Result Retrieval: Once the status is marked as finished, the skill retrieves the JSON output containing text reports, image paths, and download links.
- Delivery: The agent presents the Markdown-formatted analysis report, attaches the generated visual artifacts, and provides an edit URL for manual adjustments.
ChartGen AI Setup
To get started with this skill for Openclaw Skills, ensure you have Node.js (version 14 or higher) installed and follow these steps:
- Obtain API Key: Visit https://chartgen.ai/chat to generate your API key.
- Configure Environment: Set your key in your terminal or profile.
export CHARTGEN_API_KEY="your_api_key_here"
- Install Dependencies: Ensure the
chartgen_api.jstool is placed in your tools directory and accessible by your AI agent.
ChartGen AI Data Schema & Taxonomy
The skill manages data through a structured JSON response and local file storage. Key data components include:
| Attribute | Description |
|---|---|
text_reply |
The primary Markdown-formatted analysis report. |
artifacts[] |
An array containing artifact_id, image_path, and title. |
edit_url |
A web link to modify the visualization on the ChartGen platform. |
download_path |
The local path for generated .pptx or data files. |
preview_paths |
A list of image paths for individual PowerPoint slides. |
ChartGen AI Advanced Features
- Supports multi-file joins for complex cross-referenced data analysis (CSV, XLS, XLSX, TSV).
- Native support for background execution and cron-based polling to prevent UI blocking during long-running tasks.
- Multi-modal output capability including PNG images, interactive edit URLs, and raw HTML content.
- Language-agnostic interaction logic that adapts its confirmation and reporting style to the user's input language.
- Integrated error handling for API quotas, version upgrades, and technical troubleshooting.
SKILL.md
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