Download and install the latest version of Filestar.
Right click on one or more Prf file(s) on your desktop and select Convert with Filestar.
Type convert to jxr in the search box.
Press Convert.
Or let an AI agent do it: filestarcli -i photo.prf -c "convert to jxr" (how).
Documents - File Explorer─☐✕
This PC › Documents
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Desktop
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.prfContract.prf
.xlsxBudget.xlsx
.pdfReport.pdf
.pngLogo.png
Filestar*Help✕
Drop files here to get started
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Let your AI agent convert PRF to JXR
Claude Code, Codex, Cursor and other agents can do this on your computer with Filestar. Your files stay on your machine.
Install Filestar and add it to your agents:
npm install -g filestar
filestarcli agent install
Then ask your agent:
“Convert the PRF files in my Downloads folder to JXR”
Or run it yourself:
filestarcli -i photo.prf -c "convert to jxr"
Runs on your computer, so your files stay on it. Works on Windows, macOS and Linux. 50 free conversions with the npm install, no account needed.
Can my AI agent convert PRF to JXR?
Yes. Install the Filestar CLI with npm install -g filestar and your agent can run filestarcli -i photo.prf -c "convert to jxr" on your computer, so your files stay on it.
The Polychrome Recursive Format (PRF) is a specialized file format used primarily in the context of advanced image processing and computer graphics. It is designed to efficiently store and manipulate images with high color depth, supporting a wide range of colors and gradients. The "recursive" aspect of the format refers to its ability to apply iterative processes for image compression and decompression, allowing for high-quality images at lower file sizes. PRF files are utilized in applications where precise color representation and image fidelity are critical, such as digital art, professional photography, and scientific visualization.
Image stored in the JPEG XR format, which was originally developed by Microsoft for Windows Media software; supports deep color images with 48-bit RGB; used for high-resolution professional image editing; also supports lossless and lossy compression.
