How to Install and Use Code Summary

You just got handed the keys to a codebase. Maybe you're starting a new job. Maybe a colleague left and now their code is your problem. Maybe you're staring at your own code from eight months ago and wondering what past-you was thinking.

Whatever brought you here, you need to understand this code. Fast.

Code Summary exists for exactly this moment. It's a GitHub app that uses AI to analyze your repositories and generate documentation automatically. No manual work, no tedious wiki updates, no hoping someone remembered to write comments.

Here's how to set it up.

The 5-Minute Setup

Step 1: Create Your Account

Head to dashboard.codesummary.io and create an account with your email.

Step 2: Connect Your GitHub Account

Once you're in, you'll need to connect your GitHub account. Click the button, authorize the app, and you're connected.

Code Summary needs access to read your repositories so it can analyze the code. It also needs permission to create pull requests so it can submit documentation updates back to your repos.

Step 3: Select Your Repositories

Now pick which repositories you want documented. You can:

Select specific repos one by one
Connect an entire organization
Mix and match however you want

Start with one repo if you want to test things out. You can always add more later.

Step 4: Watch the Magic Happen

Once you've selected your repos, Code Summary gets to work. It analyzes your codebase—the structure, the patterns, how things connect—and generates documentation.

From here on out, every time you push code, the documentation updates automatically. Your docs and your code stay in sync without you lifting a finger.

What You Get

So what does Code Summary actually produce? Here's what to expect:

Architecture Overview — A high-level map of your codebase. What are the main components? How do they fit together? Where does data flow? This is the "lay of the land" view that helps you orient yourself in unfamiliar code.

Component Documentation — Detailed breakdowns of the key parts of your codebase. What does each module do? What are the important functions? This is where you go when you need to understand a specific piece of the puzzle.

Agent-Ready Context Files — Special documentation formatted for AI coding assistants like Cursor, GitHub Copilot, and Claude. Feed these to your AI tools and they'll understand your codebase much better, giving you more relevant suggestions and fewer hallucinations.

The Dashboard

Your Code Summary dashboard is home base. Here's what you can do there:

Monitor Generation Status — See which repos are being analyzed, which are done, and if anything needs attention.

Review Documentation — Read through the generated docs. See what Code Summary found. Get familiar with codebases you've never touched.

Manage Repositories — Add new repos, remove old ones, adjust settings as needed.

Track Usage — Keep an eye on your credits and plan usage.

Real Talk: When This Helps Most

Code Summary isn't magic. It's a tool. Here's when it really shines:

Inherited Codebases — Someone left. Their code is now your code. You have no idea what half of it does. Code Summary gives you a starting point—a map to navigate by while you figure things out.

Fast Onboarding — New developer joins the team. Instead of weeks of "hey, what does this do?" questions, they can read the generated docs and get productive faster.

Your Own Forgotten Code — You wrote it six months ago. You were in a hurry. There are no comments. Now you need to modify it and you're basically reverse-engineering your own work. Sound familiar? Auto-generated docs help here too.

AI-Assisted Development — Using Copilot or Cursor? They work better with context. Code Summary generates context files specifically designed to help AI tools understand your codebase.

Getting the Most Out of It

A few tips:

Start with your messiest repo. The one nobody wants to touch. The one with no documentation. That's where Code Summary adds the most value.

Check the generated docs. Don't just set it and forget it. Read through what gets generated. You might learn something about your own codebase.

Use the context files with AI tools. If you're using AI coding assistants, make sure to include the generated context. It makes a noticeable difference in suggestion quality.

Add more repos over time. Start small, see the value, then expand. Eventually you'll want everything documented.

Get Started

Ready to stop guessing and start understanding?

Your codebase has stories to tell. Let's help you hear them.