QueryTrace llms.txt Generator
Generate a real llms.txt file for any site
What it does
Turns out most sites don't have an llms.txt file. This tool writes you one. Enter your domain, we read your sitemap and up to twelve of your real pages, and write a clean, spec-compliant llms.txt grouped into sections, using only pages we actually found. Nothing invented. Copy it or download it. Free, no signup.
Generate a clean llms.txt file for any website. We map the site, read the key pages, and write a spec-compliant file you can copy or download. Free, no signup.
We map your site, read the key pages, and write a clean llms.txt you can copy or download. Free, no signup required. We start from your sitemap, or your homepage's links if there's no sitemap. Up to twelve pages, so the file reflects what's actually on your site. A clean, spec-compliant llms.txt grouped into sections, using only the real pages we found. Copy it or download it. It's a plain text file, written in Markdown, that lives at yoursite.com/llms.txt. It gives AI models a short, structured map of your site: what it is, and links to the pages that matter most. We find your sitemap (or, if there isn't one, the links on your homepage), read up to twelve of your real pages, and use their…from querytrace.co
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LLMs.txt Generator5d ago · nexiatools.com · ▲2Instantly generate standard llms.txt files for AI models
- PLProvide LLMs markdown documentation of libraries and frameworks2025 · github.com · ▲6
Hey HN! We realised that LLMs are great at generating code for super popular libraries like React. But they kinda suck at using less popular/newly released libraries, forcing us to stick to established tools and hindering innovation. There is already a standard for creating documentation for LLMs (llmstxt.org), but in my experience the implementations have not been great so far. `llms.txt` works as a good index of the available pages, but in many cases they link to HTML pages. This is a waste for LLMs to parse through (For example, Hono's [best…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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