LLM Context Window Packer
Pack files and text into an LLM context window (128k/200k/1M tokens) with per-file toggles, token estimates, and XML-tagged output. Free and offline.
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What is LLM Context Window Packer?
LLM Context Window Packer loads files and text blocks, estimates token counts, and produces an XML-tagged bundle optimized for pasting into LLM chat interfaces. Per-file toggles let you include or exclude content, and the context window selector (128k/200k/1M) shows whether you fit.
Key Benefits
- Paste-ready bundles for chat interfaces without file upload
- Token estimates prevent context window overflow
- Per-file toggles make iteration fast and precise
- XML tagging helps LLMs distinguish between sources
- Everything runs locally - files stay on your device
Common Use Cases
- •Sharing code context with ChatGPT, Claude, or other AI assistants
- •Preparing documentation bundles for AI-powered code review
- •Combining research papers and notes for AI-assisted analysis
- •Packing project files for AI-assisted debugging sessions
How to Pack Files for LLM Context
- Load your files: Select the files you want to include, or add text blocks manually.
- Toggle and tune: Include or exclude files and watch the token count update against your chosen context window.
- Copy the bundle: Copy the XML-tagged bundle and paste it directly into your LLM chat interface.
Key Features
- Load multiple files or add inline text blocks
- Per-file include/exclude toggles for context curation
- Estimated token counts based on character length
- Context window selection: 128k, 200k, or 1M tokens
- XML-tagged bundle output ready for any chat interface
- 100% client-side - files never leave your device