Generate animated trend charts and static overview images from time-series data using custom dark theme styling.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install chart-animation
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 chart-animation 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 chart-animation?
The chart-animation skill is a powerful developer utility designed to convert raw time-series JSON data into compelling visual media. Integrated into the Openclaw Skills family, it automates the creation of high-quality dark-themed GIF and MP4 animations alongside a clean, multi-panel static overview image.
This tool is particularly useful for engineers and researchers who want to visualize trends, metrics, and data cycles without writing custom rendering scripts every time. It uses production-grade Python libraries to parse structure, compute responsive labels, and output presentation-ready assets in seconds.
chart-animation Use Cases
- Creating dynamic visualization assets of system metrics or business performance for markdown documentations and status updates.
- Visualizing historical or real-time IoT sensor telemetry data as smooth animated trend charts.
- Presenting multi-variable comparative time-series statistics in slides or high-visibility presentations.
How chart-animation Works
- The user supplies a structured JSON input file containing dates, values, and hex code colors for up to 4 data series.
- The skill automatically parses the coordinates, configuring dynamic X-axis labels and calculating optimal Y-axis bounds.
- Using matplotlib and numpy, individual frames are plotted frame-by-frame matching the specified frames per second (FPS).
- The frames are bundled into a sleek animated GIF using Pillow, or encoded into high-quality MP4 using system ffmpeg.
- Simultaneously, a static grid-style PNG overview is generated, highlighting maximum and minimum thresholds.
chart-animation Setup
System & Python Dependencies
Ensure you have Python 3.8+ installed. Install the required visualization and processing libraries:
pip install matplotlib numpy pillow
To export MP4 files, ensure FFmpeg is installed on your operating system:
# macOS
brew install ffmpeg
# Ubuntu/Debian
sudo apt install ffmpeg
Running the Tool
Pass your structured JSON data directly to the command line interface:
chart-animation --data data.json --output ./charts --title "Revenue Growth" --fps 15
chart-animation Data Schema & Taxonomy
Input JSON Schema
The input schema relies on a metadata block, a sequence of dates, and defined series:
| Section | Sub-property | Description |
|---|---|---|
metadata |
generated_at, source |
Optional tracking properties for the dataset source. |
dates |
Array of strings | Ordered labels corresponding to points on the X-axis. |
series |
values, color |
Contains numerical arrays and specific hex codes for rendering lines. |
Generated Assets
The designated output directory will contain:
animation.gif: The animated visualization asset.animation.mp4: MP4 recording of the trends (requires ffmpeg).overview.png: A multi-panel static dashboard showing metrics with min/max indicator flags.
chart-animation Advanced Features
- Auto-Detect Core Boundaries: Automatically scales values to match data ceilings and floors.
- Responsive Date Formatting: Automatically wraps and scales dense dates on the X-axis grid.
- Sleek Presentation Theme: Styled out-of-the-box with a high-contrast dark theme.
- Grid-Layout Support: Renders up to 4 independent data categories in a well-proportioned 2x2 grid in the overview chart.
- Adjustable Parameters: Easily modify height, width, title override, and frames-per-second via command-line switches.
SKILL.md
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