LLM Context Compiler
Turn code repositories and project directories into token-optimized AI prompts for ChatGPT, Claude, and Gemini with instant token estimation.
🔒 100% Local Processing. No uploads.
Drop Your Codebase Here
Drag and drop a folder or select files to compile them into a context prompt for LLMs.
Compiler Settings
We already ignore node_modules, .git, build folders, and hidden env files by default.
Codebase to Prompt — Convert GitHub Repos & Code into AI-Ready Context
The LLM Context Compiler simplifies feeding full multi-file codebases and project directories into Large Language Models like ChatGPT, Claude 3.5 Sonnet, and Gemini 1.5 Pro. It automatically filters out non-essential assets (like node_modules, build artifacts, lockfiles, and binaries) and produces a clean, token-efficient markdown context bundle with real-time token estimation.
Why Developers Use LLM Context Compiler
Smart Noise Filtering
Automatically ignores heavy dependency trees, binary files, minified bundles, and SVG sprites to conserve prompt token limits.
Context Window Token Estimator
Calculates approximate token usage to ensure your codebase fits within 128k, 200k, or 1M context windows.
100% Client-Side Privacy
Your proprietary intellectual property and source code never leave your browser. Zero backend telemetry.
Pre-Built Prompt Templates
Inject structured instructions for Architecture Review, Bug Hunting, Test Generation, or Security Audits with one click.
How to Prepare Your Codebase for AI Prompts
- 1
Upload Project Files or Directory
Drag your project folder or paste individual file snippets into the compiler.
- 2
Customize File Filters
Toggle exclusion presets for node_modules, .git, test suites, or package-lock files.
- 3
Select Task Template
Pick a prompt template (e.g. Code Refactoring, Explaining Logic, Unit Test Authoring).
- 4
Copy Formatted Context
Click Copy Prompt to paste the clean markdown bundle directly into ChatGPT or Claude.
Frequently Asked Questions
Is my code uploaded to external servers?
No. The file parsing, token estimation, and markdown compilation happen 100% inside your local browser memory.
How does token estimation work?
The tool computes subword tokens using standard GPT/Claude BPE heuristics, giving you accurate estimates before submitting prompts.
Can I use this for full GitHub repositories?
Yes! Simply unzip or drag your cloned repository folder directly into the compiler.
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