Prompt Token Splitter - Split Long Texts for LLM Context Limits
Despite expanding context windows, feeding an entire 500-page book or a massive legacy repository into a single prompt often causes memory truncation, catastrophic attention degradation (the "Lost in the Middle" problem), and astronomical per-call costs. The standard engineering solution is sequential batching: dividing the payload into logical continuum prompts (Part 1 of 5, Part 2 of 5) instructing the model to hold context progressively.
When to Use This Tool
- Analyzing Entire Code Repositories: Feed a 20,000-line monolithic codebase to Claude or ChatGPT without hitting hard token limits.
- Long-Form Book & Transcript Summarization: Process 3-hour podcast transcripts or full ebook chapters sequentially.
- Overcoming "Lost in the Middle" Degradation: Prevent model hallucination caused by dense context overload in ultra-long single prompts.
- Budget Control via Chunked Prompts: Process documents in modular stages allowing human-in-the-loop validation between parts.
How to Use
- Paste Massive Content: Paste your long text, book chapter, or concatenated codebase into the input editor.
- Set Target Token Limit: Choose chunk size based on your model (e.g. 4,000 tokens for GPT-4o mini, 16,000 for Claude).
- Configure Continuum Instructions: Toggle sequential continuation headers: "This is Part X of Y. Do not finish analysis until the final part."
- Copy Part-by-Part: Copy each modular chunk sequentially to send to your AI model.
Input & Output Example
Input:
Text length: 50,000 tokens, Split Limit: 15,000 tokens
Output:
Successfully split into 4 parts.
Part 1: "[Part 1 of 4] Read and hold context...
...
[End of Part 1]"
Frequently Asked Questions (FAQ)
Q. Why do continuum instructions matter when splitting prompts?
A. If you paste a severed chunk of text without context, the LLM will hallucinate an immediate answer assuming that was the entire input. Continuum headers explicitly instruct the model to withhold conclusions until all parts are ingested.
Q. Does it split across mid-word boundaries?
A. No. The splitting engine respects sentence boundaries, paragraphs, and markdown headings to ensure ideas are never chopped in the middle of a sentence.
Q. Is there a limit on how much text I can paste?
A. Because splitting executes in browser memory, you can paste dozens of megabytes (hundreds of thousands of words) without crashing.
Engineering & Privacy Notes
- Uses intelligent semantic boundary detection (paragraphs > sentences > words) for natural splitting.
- Runs completely offline on your device with zero cloud storage.
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