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TokenPig converts documents into clean, structured Markdown built specifically for LLM and RAG workflows โ ChatGPT, Claude, Gemini, and retrieval pipelines.
Raw PDF, Word, PowerPoint and Excel exports carry a lot of formatting noise โ repeated headers, broken tables, inconsistent whitespace โ that eats into an LLM's context window without adding useful information. Cleaning that up manually is tedious, and general-purpose converters weren't built with token efficiency in mind.
Researchers, consultants, and students who regularly paste documents into ChatGPT or Claude and want cleaner, cheaper context โ plus developers and teams building retrieval-augmented generation pipelines who need reliable document-to-Markdown conversion, with an API for automation.
Compared to open-source libraries like MarkItDown or Docling, TokenPig is built for people who want a ready-to-use tool with no setup, along with visibility into token savings โ while still offering an API for teams that want to integrate it into their own pipeline.
TokenPig
MarkdeepTokenPig's answer
TokenPig started from a recurring frustration: pasting PDF or Word exports into an LLM and watching layout noise โ repeated headers, broken tables, stray whitespace โ burn through the context window before the actual content even got read. TokenPig was built to solve that specific problem: clean, structured Markdown output plus visibility into the tokens saved.
TokenPig's answer
Two main groups: individuals who regularly feed documents into ChatGPT or Claude and want cleaner, cheaper context (researchers, consultants, students), and developers/teams building RAG pipelines who need reliable document-to-Markdown conversion via API.
TokenPig's answer
TokenPig focuses specifically on token efficiency, not just format conversion. Alongside clean Markdown output, it shows an estimated token savings for every conversion, so users can see exactly how much context window they're recovering before pasting a document into ChatGPT, Claude or Gemini โ something general-purpose converters don't surface.
TokenPig's answer
TokenPig runs entirely in the browser โ no Python setup, no libraries to install, no code to maintain. That makes it accessible to non-developers (consultants, researchers, students) while still offering batch processing and an API for teams that want to automate document ingestion at scale.
TokenPig's answer
TokenPig's answer
Built as a modern web application using Next.js and TypeScript, with a focus on fast, reliable document processing entirely server-side โ no client installation required.
Based on our record, Markdeep seems to be more popular. It has been mentiond 34 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Markdeep[1] also supports drawing diagrams from ASCII arts. It's pretty good. [1] https://casual-effects.com/markdeep/. - Source: Hacker News / 6 months ago
There's also Markdeep https://casual-effects.com/markdeep/. - Source: Hacker News / 7 months ago
I've taken to using Markdeep [1] for this. You write your markdown file, but add the code snippet at the bottom of yor document and save it with a .md.html extension. Then when you double-click it it opens and renders in your browser. I save my notes in a Google Drive, and it's now replaced all the note taking apps I've tried over the years [1] https://casual-effects.com/markdeep/. - Source: Hacker News / 8 months ago
BTW: If you want "Turn Markdown into HTML at runtime" there's https://casual-effects.com/markdeep/. - Source: Hacker News / 12 months ago
I host the Markdeep library locally as well. Though overtime I've added some features, e.g. To make anchoring linking easier. [1] https://casual-effects.com/markdeep/. - Source: Hacker News / over 1 year ago
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