DhanushNehru

Reveal the skeleton of your codebase — turn any folder of code, docs, and assets into a blazing-fast queryable knowledge graph. Built in Rust.

13
3
100% credibility
Found Apr 12, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Rust
AI Summary

codeskeleton is a standalone tool that scans a directory of code files in languages like Python, JavaScript, Rust, and others to generate an interactive visualization, report, and data file revealing structural relationships such as imports, calls, and clusters.

How It Works

1
🔍 Discover codeskeleton

You find a handy tool that reveals the hidden connections in any folder of code, making complex projects easy to understand.

2
📥 Set up the tool

Download this free single-file helper and place it on your computer – ready to use in moments.

3
📁 Pick your project

Choose the folder containing the code you want to map out.

4
🚀 Start the scan

Run the tool on your folder and it quickly reads every file to build a map of how everything links together.

5
📊 Get your outputs

A new folder appears with a colorful interactive map, a summary report, and saved data for later.

6
🔗 Dive into the graph

Open the map to click nodes, search names, filter groups, and spot key hubs and unexpected links.

💡 Master your code

You now see the big picture of your project's structure, communities, and smart next questions – all in plain sight.

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Star Growth

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AI-Generated Review

What is codeskeleton?

codeskeleton scans any folder of code, docs, and assets to reveal the skeleton of your codebase as a blazing-fast queryable knowledge graph. Run `codeskeleton .` and it extracts structural elements like classes, functions, imports, and calls across Python, JavaScript/TypeScript, Rust, Go, Java, and C, then outputs an interactive vis.js graph.html, a detailed GRAPH_REPORT.md with god nodes and communities, plus graph.json for later queries. Built in Rust as a single binary with zero runtime dependencies, it skips unchanged files via SHA256 caching for incremental runs.

Why is it gaining traction?

It stands out with parallel tree-sitter parsing for speed on large repos, automatic community detection, and "surprising connections" that highlight hidden dependencies—features you see instantly in the dark-themed interactive viz with search and filters. No LLMs or heavy setups needed; just install via Cargo and get actionable insights like suggested refactor questions. Devs hook on the god nodes revealing over-coupled hubs without manual grep.

Who should use this?

Codebase archaeologists onboarding to legacy monorepos, tech leads auditing microservices for tight coupling, or refactoring teams mapping call graphs in polyglot projects. Ideal for Rust/Go devs analyzing mixed JS/Python stacks, or anyone ignoring vendor/node_modules via .cographignore.

Verdict

Early alpha with 13 stars and 1.0% credibility score—docs are solid but lacks broad tests and more languages; try on toy projects first. Worth watching for its clean CLI and viz if you need quick skeleton reveals without bloat.

(198 words)

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