A professional utility for dumping real-time STM32 LCD framebuffers via J-Link and converting raw SDRAM data into PNG images.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install framebuffer-dump
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 framebuffer-dump 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 Framebuffer Dump?
The Framebuffer Dump skill is a specialized technical workflow designed for embedded developers working with STM32 hardware. By leveraging J-Link hardware debuggers, this skill allows users to extract the exact on-device rendered frame directly from SDRAM. Unlike physical photography, this method ensures zero camera distortion, providing a perfect digital replica of the device's display buffer.
Integrating this into your Openclaw Skills library enables high-fidelity visual regression testing and pixel-perfect comparisons against design mockups like Figma. It bridges the gap between hardware rendering and software design validation by automating the transition from raw binary data to standard image formats.
Framebuffer Dump Use Cases
- Performing pixel-perfect visual comparisons between physical device displays and Figma designs.
- Generating high-quality snapshots for UI/UX documentation without camera glare or distortion.
- Debugging LCD driver issues by inspecting the raw data stored in SDRAM.
- Automating visual regression testing in embedded development pipelines using Openclaw Skills.
How Framebuffer Dump Works
- The skill identifies the target device parameters, including the framebuffer base address (e.g., 0xD0000000) and display resolution.
- A J-Link command file is dynamically generated using a local template to specify the memory range and output path.
- The JLinkExe utility is triggered in a non-GUI mode to perform a high-speed memory dump of the raw framebuffer binary.
- A Python processing script parses the raw binary data, applying the correct pixel format (such as RGB888) and dimensions.
- The final PNG image is generated, providing a clear visual representation of the device screen.
Framebuffer Dump Setup
To configure this skill within your Openclaw Skills environment, ensure you have J-Link software and Python 3 installed. Use the following commands as a guide:
# Ensure J-Link tools are in your PATH
# Prepare the J-Link command file from the provided template
# Run the dump command
JLinkExe -NoGui 1 -CommandFile /tmp/jlink_dump_fb.jlink > /tmp/jlink_dump_fb.log 2>&1
# Convert the binary dump to PNG
python3 scripts/dump_fb.py --in ./fb_dump.bin --out ./output.png --width 604 --height 1024 --stride 3
Framebuffer Dump Data Schema & Taxonomy
The skill manages data through a specific pipeline involving raw memory mappings and image metadata:
| Attribute | Default Value (PRO2) | Description |
|---|---|---|
| Memory Address | 0xD0000000 | The base address in SDRAM where the framebuffer resides. |
| Resolution | 604x1024 | The pixel dimensions of the target display. |
| Pixel Format | RGB888 | 24-bit color depth (3 bytes per pixel). |
| Dump Size | 0x1C5000 | Total byte size calculated as Width * Height * Stride. |
| Output Format | .bin -> .png | Transition from raw binary data to standard lossless image. |
Framebuffer Dump Advanced Features
- Support for custom resolution and stride parameters to accommodate different display controllers.
- Placeholder replacement logic in J-Link templates for dynamic device targeting (e.g., {{DEVICE}}, {{SPEED_KHZ}}).
- Integrated troubleshooting logic for pixel format verification (BGR vs RGB) and memory alignment checks.
- Headless execution capability for integration into automated CI/CD workflows for embedded Openclaw Skills.
SKILL.md
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