# Getting Started

## What This Project Does
This repository currently appears to be a very small or newly initialized codebase, with no discoverable modules or classes surfaced by the available repository summary. In practice, that usually means the most useful first step is to understand the repo's top-level layout, configuration files, and any surrounding docs or build scripts before looking for implementation details.

## Recommended Reading Order
1. **Project overview or README** — start with the main README or landing page for the team’s intent, setup steps, and any product context.
2. **Configuration files** — read the files that control builds, tooling, and environment behavior so you know how the project runs.
3. **Source entry points** — inspect the top-level source directories and any bootstrapping files once you understand the repo shape.
4. **Task- or module-specific docs** — after the basics, follow the docs for the subsystem you need to modify.

## Key Entry Points
There are no highly referenced classes identified in the current repository summary. If you are looking for the first place to start in code, focus on top-level files that usually act as entry points:
- Repository root files such as [`README.md`](README.md)
- Build and dependency manifests such as [`package.json`](package.json), [`pyproject.toml`](pyproject.toml), or similar
- Application bootstrap files under the main source directory, if present

## Project Structure
The current repository summary reports no sub-modules at the root level, so treat the project as a flat or lightly organized codebase until you confirm otherwise. Start by listing the top-level directories and then trace inward from the files that define runtime behavior, tests, and build tooling.

A practical way to navigate the codebase is:
- **Root** — repository-wide docs, build config, and shared tooling
- **Source directories** — implementation code, if present
- **Tests** — unit, integration, or end-to-end coverage
- **Scripts / tooling** — developer helpers, CI utilities, and automation

## Configuration
Look for the usual project-wide control files at the repository root:
- [`package.json`](package.json) or [`pnpm-lock.yaml`](pnpm-lock.yaml) / [`package-lock.json`](package-lock.json) — dependencies and scripts
- [`pyproject.toml`](pyproject.toml), [`requirements.txt`](requirements.txt), or [`poetry.lock`](poetry.lock) — Python packaging and dependencies
- [`tsconfig.json`](tsconfig.json) — TypeScript compiler settings
- [`Dockerfile`](Dockerfile) or [`docker-compose.yml`](docker-compose.yml) — container and local environment setup
- CI files such as [`.github/workflows`](.github/workflows) — automated checks and release behavior

These files are the quickest way to learn how the project is built, tested, and run locally.

## Common Patterns
Because the repository summary does not expose specific classes or modules yet, the safest onboarding approach is to expect standard engineering conventions:
- Prefer reading from the outermost entry points inward
- Trace configuration first, then runtime code, then tests
- Look for patterns repeated across files rather than single-file behavior
- Use the existing folder structure and naming conventions as your guide when adding new code

## Where to Go Next
If you are new to the project, your next steps should be:
1. Find the main README and setup instructions.
2. Identify the primary runtime entry point.
3. Locate the test suite and run the smallest relevant test command.
4. Follow the code path for one feature end-to-end before making changes.

If the repository grows additional modules or documented abstractions later, update this page to name the real entry points and replace the generic startup guidance with concrete file links.