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Code2Prompt is a powerful context engineering tool designed to ingest codebases and format them for Large Language Models. Whether you are manually copying context for ChatGPT, building AI agents via Python, or running a MCP server, Code2Prompt streamlines the context preparation process.
cargo install code2prompt
To enable optional Wayland support (e.g., for clipboard integration on Wayland-based systems), use the wayland feature flag:
cargo install --features wayland code2prompt
brew install code2prompt
pip install code2prompt-rs
Once installed, generating a prompt from your codebase is as simple as pointing the tool to your directory.
Basic Usage: Generate a prompt from the current directory. Output goes to stdout by default; use -c to copy it to the clipboard.
code2prompt .
Save to file:
code2prompt path/to/project --output-file prompt.txt
Teach your coding agent to install and use code2prompt for repository navigation and scoped context gathering with the Skills CLI:
npx skills add mufeedvh/code2prompt
The code2prompt skill helps agents reduce exploration
round trips: inspect a compact map of functions and classes using sem-core, then
read relevant source files and tests together. It includes a map template and
installation instructions for the optional entity-map feature, with a directory
map fallback for standard builds. The code2prompt CLI is installed separately.
The installer adds the skill folder and its template to your agent. It may clone the repository temporarily to retrieve them; the rest of the repository is not installed as part of the skill.
To install it globally for a specific agent, for example Codex:
npx skills add mufeedvh/code2prompt --skill code2prompt --agent codex --global
Code2Prompt is more than just a CLI tool. It is a complete ecosystem for codebase context.
Check our online documentation for detailed instructions
Code2Prompt transforms your entire codebase into a well-structured prompt for large language models. Key features include:
- Terminal User Interface (TUI): Interactive terminal interface for configuring and generating prompts
- Smart Filtering: Include/exclude files using glob patterns and respect
.gitignorerules - Flexible Templating: Customize prompts with Handlebars templates for different use cases
- Automatic Code Processing: Convert codebases of any size into readable, formatted prompts
- Token Estimates: Estimate prompt size using parallel per-file token counts and estimated template overhead, including optional line numbers. The full rendered prompt is not re-tokenized, and the estimate excludes the JSON output envelope.
- Smart File Reading: Simplify reading various file formats for LLMs (CSV, Notebooks, JSONL, etc.)
- Git Integration: Include diffs, logs, and branch comparisons in your prompts
- Blazing Fast: Built in Rust for high performance and low resource usage
Stop manually copying files and formatting code for LLMs. Code2Prompt handles the tedious work so you can focus on getting insights and solutions from AI models.
Refer to the documentation for detailed installation instructions.
Download the latest binary for your OS from Releases.
Requires:
git clone https://github.com/mufeedvh/code2prompt.git
cd code2prompt/
cargo install --path crates/code2prompt
Licensed under the MIT License, see LICENSE for more information.
If you liked the project and found it useful, please give it a ⭐ !
Ways to contribute:
- Suggest a feature
- Report a bug
- Fix something and open a pull request
- Help me document the code
- Spread the word

