AI coding assistants are much more useful when they can see the relevant parts of a project instead of just a single file or a few pasted snippets.
The problem is getting that context into the AI in the first place.
For a small project, it is easy enough to copy a few files into Claude or ChatGPT. With a larger project, things become messy pretty quickly. There may be hundreds of files, dependency directories, build output, generated files, binaries, lock files, and other content that an AI model does not really need to see.
Manually sorting through all of that takes time, and it is easy to leave out something important.
Repoprep is a browser-based tool designed to simplify that part of the workflow. It takes a project folder, ZIP archive, or collection of files and turns the useful content into a single structured context file that can be given to an AI tool.
What is Repoprep?
Repoprep packages a project into a format that is easier to provide to AI coding assistants.
Instead of doing this:
Open file → copy → paste → open another file → copy → paste → repeat
the workflow becomes:
Select a project → review the files → generate the context → paste or upload
The generated output contains the project structure first, followed by the contents of the selected files with their paths clearly labelled.
This makes it easier for an AI model to understand how the files relate to one another.
The output is plain text, so it can be used with Claude, ChatGPT, Gemini, Cursor, GitHub Copilot, Mistral, or other tools that accept text or file input.
What happens to the project files?
One of the main design choices in Repoprep is that local files are processed in the browser.
A project folder or ZIP does not need to be uploaded to a Repoprep server for processing. The browser reads the files, filters them, extracts their contents, and creates the final context document locally.
That makes the tool useful for developers who do not want to upload a private codebase to another service just to prepare an AI prompt.
Repoprep does not need an account for the free workflow.
For Pro licence verification, an email address and licence information are used for the purchase verification process, but the project files themselves are processed locally.
What gets included and excluded?
A project contains a lot more than the source code you actually want an AI model to see.
For example, a typical JavaScript or TypeScript project may contain:
- node_modules
- .git
- build output
- .next
- dist
- build
- cache directories
- lock files
- source maps
- images and other binary files
Including all of that would make the context unnecessarily large.
Repoprep automatically filters common sources of noise while keeping the files that are more likely to be useful for development work. Sensitive files such as .env are also blocked automatically.
The exact files can still be reviewed before generating the final output, so the result does not have to be an all-or-nothing export.
The generated context file
The output is intentionally simple.
A typical context file looks roughly like this:
===== PROJECT STRUCTURE =====
my-project/
├── src/
│ ├── App.tsx
│ └── index.ts
├── package.json
└── README.md
===== FILE CONTENTS =====
--- src/App.tsx ---
...file contents...
--- src/index.ts ---
...file contents...
--- package.json ---
...file contents...
The directory tree gives the AI a quick overview of the project, while the labelled file sections provide the actual source content.
This format also makes the resulting context readable to a person. You can open the generated file and see exactly what is being passed to the AI.
Token size matters
A context file is only useful if it fits within the limits of the AI model being used.
Repoprep includes a token count estimator in the Pro version so larger projects can be checked before the generated context is pasted into an AI conversation.
The count is an estimate rather than a model-specific guarantee. Tokenization differs between models, so it is better used as a practical guide when deciding how much of a project to include.
For smaller projects, you may not need this at all. For larger repositories, it becomes much more useful.
More than source code
Repoprep is not limited to JavaScript or TypeScript projects.
It supports a wide range of code and text formats, including common files used with Python, Go, Rust, Java, C/C++, SQL, HTML, CSS, JSON, YAML, Markdown, shell scripts, and others.
It can also extract text from formats such as PDF, DOCX, and XLSX.
Binary files such as images are skipped rather than being treated as source text.
This makes the workflow useful outside normal software repositories as well. A project folder can contain documentation, configuration, specifications, and other text-based material that may be relevant to an AI-assisted task.
GitHub and GitLab workflows
There is also a Chrome extension for working directly from repository pages.
Instead of downloading a repository first, the extension can be used from GitHub or GitLab to select files and generate an AI-ready context from the repository.
This is particularly useful when working with an unfamiliar codebase or when you want to inspect a repository with an AI assistant without manually copying files one at a time.
For local projects, the web app can still be used directly with a folder or ZIP archive.
Who is it useful for?
Repoprep is mainly aimed at developers who regularly use AI for software development.
Some common situations include:
Debugging
Provide the relevant source files and configuration together instead of pasting them individually.
Refactoring
Give the AI enough surrounding code to understand how a component, module, or feature fits into the rest of the project.
Working with an unfamiliar repository
Generate a structured overview of the codebase before asking questions about how it works.
Code reviews
Package the relevant files into a single context that can be reviewed by an AI assistant.
Project handoffs
Create a portable snapshot of the files relevant to a particular AI session without manually assembling the context each time.
The important point is that Repoprep does not replace the AI assistant. It handles the preparation step before the actual AI conversation begins.
Free and Pro versions
The free version is intended for smaller tasks and supports up to 25 files and 2 MB per session.
The Pro version is a one-time $6 purchase, rather than a recurring subscription. It increases the limit to 200 files and 20 MB and adds the token count estimator.
The product currently follows a simple model: use the free version for smaller projects and upgrade when the larger project limits become useful.
A simpler way to get project context into AI
AI-assisted development has made it much easier to ask questions about a codebase, but the quality of the answer still depends on the context provided to the model.
For small tasks, copying a couple of files is fine.
For larger tasks, preparing that context manually can become a repetitive part of the workflow.
Repoprep is built to handle that preparation step: take the relevant project files, remove common noise, preserve the project structure, and produce one readable context file that can be used with the AI tool of your choice.
There is no installation required for the web app, and local projects can be processed directly in the browser.
Repoprep: https://www.repoprep.com/
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