How to understand a GitHub repo
A step-by-step process for making sense of any codebase you have never seen before.
Start with the README
The README is your first stop, but do not expect it to tell you everything. Most READMEs cover installation and basic usage. Few explain architecture or design decisions.
Look for: what the project does, how to run it locally, what technologies it uses, and whether there is a link to further documentation. If the README is sparse, that tells you something about the project's documentation culture.
Read the file tree before opening files
Before opening any code files, look at the directory structure. The top-level folders tell you how the project is organized.
Common patterns to look for:
- `src/` or `app/` — the main application code - `lib/` or `utils/` — shared utilities and helpers - `components/` — UI components (frontend projects) - `api/` or `routes/` — API endpoint handlers - `tests/` or `__tests__/` — test files - `config/` — configuration files - `migrations/` or `prisma/` — database schema
If the project uses a framework (Next.js, Rails, Django), the directory structure follows framework conventions. Knowing the framework tells you where to find routing, models, controllers, and views.
Identify the entry point
Every application has an entry point. Find it first.
For web applications: look at `package.json` scripts (the `dev` or `start` command tells you which file boots the app). For Next.js projects, `app/layout.tsx` or `pages/_app.tsx` is the root. For Express apps, look for `server.js` or `index.js`.
For backend services: check `main.go`, `app.py`, `Main.java`, or whatever the language convention is. The entry point shows you what gets initialized: database connections, middleware, routes, and background jobs.
Map the data flow
Once you know the entry point, trace how data moves through the system. Start from a user action (like submitting a form) and follow it through the codebase.
In a typical web app, data flows like this: browser -> API route -> handler/controller -> service/business logic -> database -> response -> browser.
You do not need to trace every path. Pick one important flow (like user authentication or the main feature) and follow it end to end. This gives you a mental model of how the pieces connect.
Check the dependency list
Open `package.json` (Node.js), `requirements.txt` (Python), `Gemfile` (Ruby), `go.mod` (Go), or `Cargo.toml` (Rust). The dependency list tells you what tools the project relies on.
Look for:
- Web framework (Express, Next.js, Django, Rails) - Database client (Prisma, Sequelize, pg, mongoose) - Authentication library (passport, next-auth, supabase) - API tools (axios, graphql, tRPC) - Testing framework (Jest, pytest, RSpec)
Each dependency is a clue about how the project works. If you see `stripe`, there is payment processing. If you see `bull` or `bullmq`, there are background jobs. If you see `socket.io`, there is real-time communication.
Look at the database schema
The database schema is often the most honest documentation in a project. It shows what data the application stores and how entities relate to each other.
Look for migration files, a `schema.prisma` file, or SQL files in a `migrations/` directory. If the project uses an ORM, the model definitions show you fields, relationships, and constraints.
The schema answers questions like: What are the main entities? How are users related to other objects? What data gets stored vs. computed?
Read the tests
Tests describe intended behavior. When documentation is missing, tests are the next best thing.
Look at test file names to understand what features exist. Read a few test cases to see how functions are expected to be called and what outputs they produce. Integration tests are especially useful because they show how multiple components work together.
If there are no tests, that is also useful information. It tells you the codebase has less safety net than you might want.
Use automated tools
Manual exploration is valuable, but it is slow. Tools can give you a structured overview in minutes instead of hours.
CodeDashboard analyzes any GitHub repository and generates an interactive dashboard with architecture diagrams, tech stack detection, data flow visualizations, and plain-English summaries. Paste the repo URL, wait 2 minutes, and get a visual map of the entire system.
Other useful tools: your IDE's "find all references" feature, GitHub's code search, and `git log --oneline` to see the commit history and understand what changed recently.
Key takeaways
- 1Start with the README and file tree, not the code.
- 2Identify the entry point and trace one data flow end to end.
- 3The dependency list and database schema are the most reliable sources of truth.
- 4Tests describe intended behavior when documentation is missing.
- 5Automated tools like CodeDashboard can generate a visual overview in under 2 minutes.
Related guides
What is codebase documentation?
The types of documentation every codebase needs, and how to create them without burning out.
How to do a code handover
The handover checklist that saves you from "just one more question" emails for the next 3 months.
How to audit a codebase
What to check before you take responsibility for someone else's code.
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