- Open the Composer / command palette with Ctrl+I (or Cmd+I on macOS).
- The Composer exposes commands such as Add Files, Edit, Refactor, Add Code, and switching models (e.g., Claude 3.5 Sonnet, GPT-4o family, Cursor Small).
- Some keybindings are intercepted by Cursor and won’t be forwarded to the terminal by default. You can rebind them if required.

.gitignore, pyproject.toml, a basic main application, and a test skeleton. Below are the key generated artifacts, the improved code, and practical tips to run and test the project reliably.
What Cursor generated (at a glance)
Generated .gitignore
Cursor created a standard Python.gitignore. Only one copy is shown here.
Project metadata (pyproject.toml)
Cursor generated a minimalpyproject.toml using hatchling and included common dev dependencies:
Example requirements.txt
Cursor added example runtime and development dependencies torequirements.txt:
main.py — scaffolded and improved
Cursor scaffolded a main entrypoint with logging. We refactored the file-processing logic into a standalone function to make it easier to test and more robust. Important fixes included: open the output file once (not inside the loop) and return processed lines for testability. Final recommended version:- Opening the output file once and writing per-line prevents repeatedly truncating the file.
- Returning the processed lines makes unit testing straightforward.
Example config.py
Cursor added a small config helper to read environment variables (common for API keys and configuration). Typically this file usesos.environ or python-dotenv to load values and keep secrets out of source control.
Create a virtual environment, install dependencies, and run
From your project root, follow these steps:src/my_project/main.py.
Cursor Composer: generating quick code and files
Cursor’s Composer can generate small helper snippets and files (e.g., a demodemo.txt or a function that reads a file). A typical iterative workflow:
- Use the Composer to create
demo.txtwith Lorem Ipsum or sample lines. - Ask Cursor to “Open demo.txt and print it line by line” and accept the generated snippet.
- Use the Composer to refactor code (for example, “Move this into a function”) and accept a suggested refactor.
- Always review generated code — fix minor issues such as indentation, function placement, or file-handling correctness.
Writing a proper unit test
Cursor generated a basic test skeleton. We updated it to match the refactoredprocess_file signature and to use pytest fixtures (tmp_path) so tests are deterministic and isolated from the repository.
Example tests/tests_main.py:
- Use
tmp_pathto avoid touching repository files and ensure tests run in isolation. - Call
process_filewith explicit temporary paths to avoid side effects. - Assert both the returned result and the output file contents.
Common testing / packaging issues and fixes
When running tests you may encounter import errors like “ModuleNotFoundError: No module named ‘my_project’”. Typical fixes:- Install your package in editable mode from the project root:
my_project is importable by pytest.
- Ensure package structure is configured correctly. If you rely on implicit namespace packages, adjust
pyproject.toml; otherwise add an__init__.py:
- Verify pytest configuration (
[tool.pytest.ini_options]) points to the tests folder and the expected test filename patterns (the generatedpyproject.tomlalready contains sensible defaults).
Debugging loops and where developer judgment matters
AI-assisted tools like Cursor can scaffold code, suggest fixes, and accelerate iteration, but they can also create back-and-forth edit loops (changed APIs, import paths, test mismatches). During this exercise we intentionally ran into loop-like issues (module import paths, function signatures vs. tests) to demonstrate how developer knowledge resolves structural problems.AI tools accelerate scaffolding and routine edits, but keep an eye on:
- Project structure and package/module paths
- Function signatures vs. tests (ensure tests reflect actual function APIs)
- File handling (open output files once, not inside loops)
pyproject.toml configuration, and import paths.
We’ll expand this into a larger application and combine multiple tools (ChatGPT, Tabnine, BlackboxAI, Cursor) to show a broader, integrated AI-assisted development workflow.