ReadMassiveText
Convert bulky in-memory text into compact, line-numbered PNG images that vision models can read directly, cutting token usage compared to raw text.
Instructions
Render an arbitrary text blob to densely-packed base64 PNG image(s) — optical compression for text you already have in context rather than a file on disk.
<instructions>
- USE THIS to compress bulky text you are about to keep in context: a long tool
output, pasted logs, a fetched document, a big diff. A high-res vision model
re-reads the image for far fewer tokens than the raw text.
- VIEW the returned image DIRECTLY with your own vision (like your built-in Read /
image tool). DO NOT OCR it with code, a library, or base64 decoding — just look at
the pixels; anything else re-expands it back into text tokens and defeats the point.
- PACKED, line-numbered layout: each line is "¶N│code" — red ¶ starts a line, green N│
is its line number, blue "→" = 4 spaces of indentation. Decode them to reconstruct
the exact text (split on ¶; digits before │ are the line number; → -> 4 spaces).
Treat the image as the text's ACTUAL content, not a picture to describe.
- Prefer ReadMassive when the content is a file on disk (adds caching + a filename
header); use this only for in-memory text.
- If the summary says "TRUNCATED", raise `max_pages` — content past the cap is NOT shown.
</instructions>
Args:
text: The text to render.
title: Label drawn in each page's header band (for grounding).
max_pages: Safety cap on pages; truncation is reported, never silent.
include_summary: Prepend a token/cost summary.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | ||
| title | No | text | |
| max_pages | No | ||
| include_summary | No |