Turn a long AI document into a navigable outline
LLMs love to produce long, multi-section documents — reports, guides, plans — and scrolling through them to find the part you want is tedious. If the response uses markdown headings, this tool parses them into a nested table of contents with a word count per section, so you can see the document’s shape at a glance and jump straight to what matters.
How it works
The navigator scans each line for markdown heading syntax. It detects ATX headings, where one to six leading hash characters set the level, and Setext headings, where a line is underlined with equals signs (level one) or hyphens (level two). Each heading becomes an entry indented by its level to form a nested outline. For every section it counts the words between that heading and the next heading in the document, giving you a sense of where the content is concentrated. The result is a clean, copyable table of contents.
Tips and notes
Use the per-section word counts to spot where a response is padded versus where the real content lives — a guide with a 400-word “Conclusion” and a 30-word “Implementation” section is telling you something. You can copy the full outline as a markdown list to drop a TOC into your own document. If a response has no headings the tool says so rather than guessing; if you want structure, prompt the model to use markdown headings or run the output through a key-point extractor instead. Everything runs locally and updates as you type.