Convert GitHub repo to ChatGPT context. Prepare code for AI code review. 100% local processing.
Compile your codebase into AI-optimized context. Smart exclusion, token estimation, 100% local processing.
🔒 100% Local Processing. Your code never leaves your browser.
Drag and drop a folder or select files
ToolsWallet's LLM context compiler helps you convert codebase to prompt for ChatGPT, Claude, and Gemini. This secure local code to prompt tool lets you prepare code for AI code review, compile GitHub repo for ChatGPT, and flatten project directory for AI analysis. Perfect for developers who need to upload whole project to ChatGPT, bypass token limits, and get AI code review without uploading code to external servers.
Secure local code to prompt tool - your code never leaves your browser. Perfect for proprietary codebases.
Automatically ignores node_modules, .git, .next, build folders - no manual cleanup needed
Count tokens for local codebase to fit within Claude 200K, GPT-4 128K, or Gemini 1M limits
Clone your GitHub repository locally, drag and drop the folder into our LLM Context Compiler, review the file tree, and click "Copy to Clipboard". The tool will compile your entire repo into a markdown format that ChatGPT can understand, automatically excluding node_modules and build files.
Use code minification to strip whitespace and comments, selectively exclude non-essential files using the file tree checkboxes, and monitor the token counter. Our tool estimates tokens in real-time so you can stay within ChatGPT's limits (8K for GPT-3.5, 128K for GPT-4).
Our tool generates markdown-formatted output with clear file path headers and code blocks - the exact format Claude 3 prefers. With Claude's 200K token context window, you can upload significantly larger codebases than with other AI models.
Use our LLM Context Compiler to convert your entire project into a single markdown file, copy it to your clipboard, then paste it into ChatGPT, Claude, or Gemini with a prompt like "Review this codebase for bugs, security issues, and improvements".
Code prompts exceed token limits due to: 1) Including node_modules or build files, 2) Not minifying code, 3) Including unnecessary files. Our tool automatically excludes bloat directories and offers minification to reduce token count by 30-50%.
Drag and drop your folder into the LLM Context Compiler. The tool will instantly display an estimated token count using a 4:1 character-to-token ratio, which is accurate for most AI models including GPT-4, Claude, and Gemini.
The safest way is using a 100% local processing tool like ours. Your code is compiled entirely in your browser - nothing is uploaded to external servers. This is critical for proprietary or confidential codebases.
Our tool automatically excludes common build directories (node_modules, .git, .next, dist, build, out, coverage) and sensitive files (.env, .pem, .key). You can also manually uncheck any files in the visual file tree.
Enable code minification to remove whitespace and comments, exclude test files and documentation, use selective file inclusion via checkboxes, and target AI models with larger context windows (Claude 200K, Gemini 1M vs GPT-4 128K).
Use our 100% local processing tool - your code never leaves your browser. Unlike cloud-based tools, there's no risk of your proprietary code being stored on external servers or used for AI training. All compilation happens client-side using JavaScript.