Code review style guide

If you have a custom set of best practices or conventions that you want Gemini Code Assist on GitHub to check for or follow when performing a code review, you can add a styleguide.md Markdown file to the .gemini/ root folder of your repository. Users of the enterprise version of Gemini Code Assist on GitHub can use the Google Cloud console to add style guide information for use across multiple repositories. In both cases, the style guide is treated as a regular Markdown file, and expands the standard prompt that Gemini Code Assist on GitHub uses.

Standard code review patterns

When custom style guides aren't specified, these are the main categories of areas where Gemini Code Assist focuses its code review on:

  • Correctness: Makes sure the code functions as intended and handles edge cases, checks for logic errors, race conditions, or incorrect API usage.

  • Efficiency: Identifies potential performance bottlenecks or areas for optimization, like excessive loops, memory leaks, inefficient data structures, redundant calculations, excessive logging, and inefficient string manipulation.

  • Maintainability: Assesses code readability, modularity, and adherence to language idioms and best practices. Targets poor naming for variables, functions, and classes, lack of comments or documentation, complex code, code duplication, inconsistent formatting, and magic numbers.

  • Security: Identifies potential vulnerabilities in data handling or input validation, like insecure storage of sensitive data, injection attacks, insufficient access controls, Cross-Site Request Forgery (CSRF), and Insecure Direct Object References (IDOR).

  • Miscellaneous: Other topics are considered when reviewing the pull request, like testing, performance, scalability, modularity and reusability, and error logging and monitoring.

Example style guide

The styleguide.md file does not have a defined schema. Instead, it's a natural language description of how you want Gemini Code Assist to structure its code reviews. The following code snippet is an example of a styleguide.md file:

# Company X Python Style Guide

## Introduction

This style guide outlines the coding conventions for Python code developed at
Company X. It's based on PEP 8, but with some modifications to address
specific needs and preferences within our organization.

## Key Principles

*   **Readability:** Code should be easy to understand for all team members.
*   **Maintainability:** Code should be easy to modify and extend.
*   **Consistency:** Adhering to a consistent style across all projects
    improves collaboration and reduces errors.
*   **Performance:** While readability is paramount, code should be efficient.

## Deviations from PEP 8

### Line Length

* **Maximum line length:** 100 characters (instead of PEP 8's 79).
    *   Modern screens allow for wider lines, improving code readability in
        many cases.
    *   Many common patterns in our codebase, like long strings or URLs, often
        exceed 79 characters.

### Indentation

*   **Use 4 spaces per indentation level.** (PEP 8 recommendation)

### Imports

*   **Group imports:**
    *   Standard library imports
    *   Related third party imports
    *   Local application/library specific imports
*   **Absolute imports:** Always use absolute imports for clarity.
*   **Import order within groups:**  Sort alphabetically.

### Naming Conventions

*   **Variables:** Use lowercase with underscores (snake_case): `user_name`, `total_count`
*   **Constants:**  Use uppercase with underscores: `MAX_VALUE`, `DATABASE_NAME`
*   **Functions:** Use lowercase with underscores (snake_case): `calculate_total()`, `process_data()`
*   **Classes:** Use CapWords (CamelCase): `UserManager`, `PaymentProcessor`
*   **Modules:** Use lowercase with underscores (snake_case): `user_utils`, `payment_gateway`

### Docstrings

*   **Use triple double quotes (`"""Docstring goes here."""`) for all docstrings.**
*   **First line:** Concise summary of the object's purpose.
*   **For complex functions/classes:** Include detailed descriptions of
    parameters, return values, attributes, and exceptions.
*   **Use Google style docstrings:** This helps with automated documentation generation.
    ```python
    def my_function(param1, param2):
        """Single-line summary.

        More detailed description, if necessary.

        Args:
            param1 (int): The first parameter.
            param2 (str): The second parameter.

        Returns:
            bool: The return value. True for success, False otherwise.

        Raises:
            ValueError: If `param2` is invalid.
        """
        # function body here
    ```

### Type Hints

*   **Use type hints:**  Type hints improve code readability and help catch
    errors early.
*   **Follow PEP 484:**  Use the standard type hinting syntax.

### Comments

*   **Write clear and concise comments:** Explain the "why" behind the code,
    not just the "what".
*   **Comment sparingly:** Well-written code should be self-documenting where
    possible.
*   **Use complete sentences:** Start comments with a capital letter and use
    proper punctuation.

### Logging

*   **Use a standard logging framework:**  Company X uses the built-in
    `logging` module.
*   **Log at appropriate levels:** DEBUG, INFO, WARNING, ERROR, CRITICAL
*   **Provide context:** Include relevant information in log messages to aid
    debugging.

### Error Handling

*   **Use specific exceptions:** Avoid using broad exceptions like `Exception`.
*   **Handle exceptions gracefully:** Provide informative error messages and
    avoid crashing the program.
*   **Use `try...except` blocks:**  Isolate code that might raise exceptions.

## Tooling

*   **Code formatter:**  [Specify formatter, e.g., Black] - Enforces
    consistent formatting automatically.
*   **Linter:**  [Specify linter, e.g., Flake8, Pylint] - Identifies potential
    issues and style violations.

Manage style guides across multiple repositories

If you have the enterprise version of Gemini Code Assist on GitHub, you can have one style guide apply to multiple repositories. Repositories are grouped by a Developer Connect connection, and managing their collective style guide is accomplished through the Google Cloud console.

If a repository is managed as part of a group but also has its own styleguide.md file, the repository's styleguide.md is combined with the group style guide.

The following steps show how users of the enterprise version can control one style guide across multiple repositories. These steps assume you have previously set up Gemini Code Assist on GitHub.

  1. In the Google Cloud console, go to the Gemini Code Assist Agents & Tools page.

    Go to Agents & Tools

  2. In the Agents section, locate the Code Assist Source Code Management card, and click Advanced.

    The Edit Code Assist Source Code Management pane opens.

  3. In the Connections table, click the name of the connection that you want to apply a style guide to.

    The details page for the connection opens.

  4. In the Style guide tab, add the style guide you want the repositories associated with this connection to use.

  5. Click Save.

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