Download and install the latest version of Filestar.
Right click on one or more Cals file(s) on your desktop and select Convert with Filestar.
Type convert to viff in the search box.
Press Convert.
Or let an AI agent do it: filestarcli -i photo.cals -c "convert to viff" (how).
Documents - File Explorer─☐✕
This PC › Documents
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Desktop
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.calsContract.cals
.xlsxBudget.xlsx
.pdfReport.pdf
.pngLogo.png
Filestar*Help✕
Drop files here to get started
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Let your AI agent convert CALS to VIFF
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 CALS files in my Downloads folder to VIFF”
Or run it yourself:
filestarcli -i photo.cals -c "convert to viff"
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 CALS to VIFF?
Yes. Install the Filestar CLI with npm install -g filestar and your agent can run filestarcli -i photo.cals -c "convert to viff" on your computer, so your files stay on it.
The CALS Raster Graphic File, having the extension .cals, is a type of image file format primarily used for the storage and exchange of digital images, especially in the context of technical and engineering documents. Developed in the mid-1980s by the United States Department of Defense, the CALS format was part of an initiative to standardize electronic document management and interchange, particularly for military and government applications.
The Visualization Image File Format (VIFF) is a specialized file format designed for storing image data. It is primarily used in scientific and technical applications where complex visualization of multi-dimensional data is required. VIFF files can store various types of data including grayscale, color, and multi-spectral images, making them suitable for tasks such as image processing, medical imaging, and remote sensing. This format supports a range of metadata, allowing for the inclusion of information about the image data, such as dimensions and color.
