tnguyen21

tnguyen21 / dw2md

Public

Crawl a DeepWiki repository and compile all pages into a single, LLM-friendly markdown file

18
1
100% credibility
Found Feb 17, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

dw2md downloads and assembles all pages from a DeepWiki project documentation site into one structured Markdown or JSON file designed for easy use with AI models.

How It Works

1
🌐 Discover DeepWiki

You find DeepWiki, a site with detailed breakdowns of open-source projects, but the info is spread across many pages with no easy way to save it all.

2
💡 Learn about dw2md

You hear about dw2md, a handy tool that pulls the entire wiki into one simple file perfect for reading or sharing with AI helpers.

3
📥 Add dw2md to your computer

You quickly get dw2md set up on your machine using your favorite method, ready to use in seconds.

4
🎯 Pick a project and grab its wiki

You name the project like tinygrad/tinygrad, and dw2md fetches the full set of pages, showing progress as it builds your complete guide.

5
Choose your sections
✅
Grab everything

Download the whole wiki at once for a complete overview.

✂️
Pick and choose

Browse the list, select sections with simple toggles, and get only what you need.

📄 Get your all-in-one file

You now have a single, neatly organized document with table of contents and easy-to-find sections, ready to read, search, or paste into an AI chat.

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Star Growth

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AI-Generated Review

What is dw2md?

dw2md is a Rust CLI tool that crawls DeepWiki repositories—auto-generated docs for GitHub repos—and compiles all pages into a single LLM-friendly markdown file. DeepWiki spreads excellent structured documentation across dozens of pages with no export option, but dw2md fetches everything via direct server calls, adding a tree-style TOC and grep-able section delimiters like `<<< SECTION: Title [slug] >>>`. Bash one command like `dw2md tinygrad/tinygrad -o wiki.md` to get a token-efficient file ready for LLM contexts.

Why is it gaining traction?

It stands out by skipping browser automation for fast, reliable fetches—no auth, retries built-in—and offers smart filtering: list TOC with `--list`, interactively select sections with `-i`, or target slugs via `-p`/`-x`. JSON output suits programmatic use, and the format optimizes for agents scanning large docs without full reloads. In a world of general crawlers like crawl4ai github or spider crawl github tools, this specializes in DeepWiki for clean, compile-ready repo docs.

Who should use this?

AI engineers building repo-aware agents or RAG systems need it to dump full DeepWiki coverage into one file for LLM prompting. Docs researchers analyzing open-source projects like tokio-rs/tokio via DeepWiki will love the selective crawls. Devs prototyping on GitHub repos benefit from piping output to clipboard or excluding fluff sections.

Verdict

Grab it if you work with DeepWiki—solid CLI, great docs, and tests make it production-ready despite 17 stars and 1.0% credibility score signaling early maturity. Install via `cargo install dw2md` and test on a repo today; it's niche but nails the job.

(198 words)

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