> ## Documentation Index
> Fetch the complete documentation index at: https://docs.coderabbit.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Code Review

> Experience CodeRabbit's automated code review by creating your first pull request

export const Hint = ({type, children, headline, tip, href, cta}) => {
  const TIPS = {
    learnings: {
      headline: "Learnings",
      tip: "Review preferences CodeRabbit learns from your chat conversations and applies automatically to future reviews.",
      cta: "Learn about Learnings",
      href: "/knowledge-base/learnings",
      content: "Learnings"
    },
    walkthrough: {
      headline: "PR Walkthrough",
      tip: "A structured comment posted by CodeRabbit at the top of every pull request, summarizing changes, sequence diagrams, review effort, and more.",
      cta: "Learn about PR Walkthroughs",
      href: "/pr-reviews/walkthroughs",
      content: "Walkthrough"
    },
    "finishing-touches": {
      headline: "Finishing Touches",
      tip: "Post-review agentic actions (Autofix, writing docstrings or unit tests, and more) you trigger from a PR comment or a checkbox in the Walkthrough.",
      cta: "See all Finishing Touches",
      href: "/finishing-touches",
      content: "Finishing Touches"
    },
    "coding-plan": {
      headline: "Coding Plan",
      tip: "A detailed, codebase-aware implementation plan CodeRabbit generates from an issue or description, ready to hand off to any coding agent.",
      cta: "Learn about Coding Plans",
      href: "/plan",
      content: "Coding Plan"
    },
    "knowledge-base": {
      headline: "Knowledge Base",
      tip: "The collected context sources CodeRabbit draws on during reviews: Learnings, Code Guidelines, issue trackers, connected MCP servers, and cross-repo analysis.",
      cta: "Explore the Knowledge Base",
      href: "/knowledge-base",
      content: "Knowledge Base"
    },
    "path-instructions": {
      headline: "Path Instructions",
      tip: "Custom review rules that only apply to files matching a glob pattern, e.g. 'src/controllers/**'.",
      cta: "Configure path instructions",
      href: "/configuration/path-instructions",
      content: "Path Instructions"
    },
    scope: {
      headline: "Scope",
      tip: "A named set of repositories, connections, and spend limits that controls what CodeRabbit Agent can access in a given Slack conversation.",
      cta: "Learn about Scopes",
      href: "/slack-agent/scopes",
      content: "Scope"
    }
  };
  const defaults = TIPS[type] || ({});
  return <Tooltip headline={headline ?? defaults.headline} tip={tip ?? defaults.tip} cta={cta ?? defaults.cta} href={href ?? defaults.href}>
      {children ?? defaults.content}
    </Tooltip>;
};

<Steps>
  <Step icon="circle-check-big" title="Integrate CodeRabbit into a GitHub repository that you own" />

  <Step title=">>> Observe CodeRabbit perform a code review of a pull request that you initiate" />

  <Step title="Converse with CodeRabbit about the code review" />

  <Step title="Prompt CodeRabbit to generate its own improvements to the pull request" />
</Steps>

## Create a pull request

Now that CodeRabbit is integrated with your repository, it's time to see it in action. You'll create a pull request with intentionally imperfect code to demonstrate how CodeRabbit identifies issues and provides actionable feedback.

The following steps guide you through creating a pull request that adds a small Python library with a few common code quality issues.

Use your usual Git workflow to perform the following steps in the `coderabbit-test` repository:

<Steps>
  <Step title="Create a branch">
    Create a branch named `add-utils`.
  </Step>

  <Step title="Create a new file">
    In that new `add-utils` branch, create a new file called `simple_utils.py`, with the following content:

    ```python theme={null}
    # simple_utils.py - A tiny utility library

    def reverse_string(text):
        """Reverses the characters in a string."""
        return text[::-1]

    def count_words(sentence):
        return len(sentence.split())

    def celsius_to_fahrenheit(celsius):
        return (celsius * 9/5) + 32
    ```
  </Step>

  <Step title="Commit the file">
    Commit the added file to the `add-utils` branch. Use any text you want for the commit message.
  </Step>

  <Step title="Create a pull request">
    Create a pull request that proposes to merge the `add-utils` branch into the `main` branch. Use any text you want for the pull request message.
  </Step>
</Steps>

After a few moments, CodeRabbit responds to the pull request using the `@coderabbitai` GitHub account. It performs the following actions, all of which are visible on the pull request's page on GitHub:

* If you didn't write a pull request summary, then CodeRabbit adds a new summary to the pull request.
* CodeRabbit posts a comment titled <Hint type="walkthrough" /> containing analysis and commentary about the content of the pull request.
* CodeRabbit attaches a detailed code review to the pull request as another comment.

Part of the review resembles the following screenshot:

<img src="https://mintcdn.com/coderabbit/D_rqUjBaYiE185JH/images/getting-started/assets/images/quickstart-comment-9310a2af173d5afbd2c74a762e6bd808.png?fit=max&auto=format&n=D_rqUjBaYiE185JH&q=85&s=159b85cdd77b56e33b809b0d3d4cb7cb" alt="An example code review comment" width="1624" height="964" data-path="images/getting-started/assets/images/quickstart-comment-9310a2af173d5afbd2c74a762e6bd808.png" />

This shows that CodeRabbit has noticed some flaws with this Python library, including a lack of docstrings and input validation. The review comment identifies these flaws, and suggests how you might improve them.