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‎docs/changelog.md

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sidebar_position: 13
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---
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## April 8, 2025
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### New Static Analysis Tools
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We've expanded our static analysis capabilities with two new tools:
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- **OXC**: A high-performance JavaScript/TypeScript linter written in Rust.
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- **Prisma Lint**: A dedicated linter for Prisma schema files to help enforce consistent conventions and best practices.
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Both tools can be configured through their respective config files or through CodeRabbit's settings page. See our [tools documentation](https://docs.coderabbit.ai/tools/tools) for more details.
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## April 1, 2025
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### Code Graph Analysis

‎docs/guides/agent_chat.md

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---
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title: Agentic Chat
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sidebar_label: Agentic Chat
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description: Learn about CodeRabbit Pro's agentic chat system
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sidebar_position: 8
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title: Chat and Agentic Chat
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sidebar_label: Chat and Agentic Chat
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description: Learn about CodeRabbit Pro's chat and agentic chat system
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sidebar_position: 3
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---
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# Agentic Chat
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# CodeRabbit Chat
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```mdx-code-block
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import ProPlanNotice from '@site/src/components/ProPlanNotice.mdx';
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Set `enabled` to false within `web_search` within `knowledge_base` within the config in order to turn this off.
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### Code Definition Integration
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CodeRabbit Chat is capable of taking definitions of code symbols from the symbol graph that CodeRabbit generates from your codebase. The CodeRabbit Chat response will indicate in its responses if it has found relevant symbols and snippets surrounding symbols in your codebase.
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Set the environment variable `ENABLE_CODE_GRAPH` in self-hosted CodeRabbit instances to turn this feature off.
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### Jira and Linear Integration
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CodeRabbit Chat can deal with existing issue tracking system integrations in order to integrate with your existing issues. For details on setting up issue tracking integrations, see our [Issue Integrations](../integrations/issue-integrations.md) guide and [Issue Creation](./issue-creation.md) guide.
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For rapid prototyping and quick fixes, CodeRabbit Chat is capable of generating code snippets in a single step.
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### Multi-Step Agentic Flow with Planning
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### Configuration Changes
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CodeRabbit is also capable of managing its own configuration settings upon request. This self-management allows the assistant to dynamically adapt to changing project requirements. By simplifying configuration updates, CodeRabbit helps users quickly adjust to new workflows or requirements without interrupting the development process.
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When facing complex coding challenges, CodeRabbit Chat supports multi-step agentic flows that involve detailed planning and execution. Once the multi-step workflow is complete, CodeRabbit can automatically issue a pull request for the changes so you can consent to the code changes or edit them.
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## Agentic Chat (Chat with Planning)
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CodeRabbit cannot perform further modifications to opened pull requests. From there, it's your turn to checkout the branch and improve it to satisfaction. We believe that this workflow provides a significant headstart to implementing code.
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When facing complex coding challenges, CodeRabbit Agentic Chat supports multi-step agentic flows that involve detailed planning and execution. Once the multi-step workflow is complete, CodeRabbit can automatically issue a pull request for the changes so you can consent to the code changes or edit them. CodeRabbit can also place changes in the existing pull request branch or create copyable snippets.
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Multi-step agentic flows are currently only available on Github pull request review comments. Multi-step agentic flows are an early access product currently.
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Agent chat can be invoked explicitly with the `@coderabbitai plan` command.
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### Configuration Changes
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CodeRabbit cannot perform further modifications to opened pull requests. From there, it's your turn to checkout the branch and improve it to satisfaction. We believe that this workflow provides a significant headstart to implementing code.
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CodeRabbit is also capable of managing its own configuration settings upon request. This self-management allows the assistant to dynamically adapt to changing project requirements. By simplifying configuration updates, CodeRabbit helps users quickly adjust to new workflows or requirements without interrupting the development process.
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Agentic Chat is currently only available on Github issue, pull request and pull request review comments. Agentic Chat is an early access product currently.
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### Help and Feedback
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‎docs/guides/commands.md

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---
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title: Commands
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sidebar_label: Commands
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description: Learn how to control CodeRabbit using commands in pull request comments
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sidebar_position: 1
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---
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# CodeRabbit Commands
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> Control your code reviews directly from pull request comments using CodeRabbit's command system. Each command starts with `@coderabbitai` followed by the specific action you want to take.
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| `@coderabbitai generate docstrings` | Generates docstrings for functions in the PR | When you need automatic documentation for your code |
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| `@coderabbitai configuration` | Shows current CodeRabbit settings | When you need to check or export your configuration |
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### Agentic Chat Commands
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| Command | Description | Use Case |
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| -------------------- | ---------------------------------------------------------- | ---------------------------------------------------- |
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| `@coderabbitai plan` | Get the agentic chat to plan an edit for previous comments | When you want CodeRabbit to change your code for you |
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### Help & Support
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| Command | Description | Use Case |

‎docs/guides/custom-reports.md

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title: Custom Reports
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sidebar_label: Custom Reports
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description: Learn how to create custom reports with CodeRabbit Pro's flexible reporting system
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sidebar_position: 8
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---
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```mdx-code-block

‎docs/guides/issue-chat.md

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title: Issue Chat
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sidebar_label: Issue Chat
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description: Learn how to use CodeRabbit's chat capabilities within issues
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sidebar_position: 10
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sidebar_position: 4
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---
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```mdx-code-block

‎docs/guides/issue-creation.md

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title: Issue Creation
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sidebar_label: Issue Creation
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description: Learn how to create issues directly through CodeRabbit
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sidebar_position: 9
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sidebar_position: 5
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---
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```mdx-code-block

‎docs/guides/linked-issues.md

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---
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title: Linked Issues
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sidebar_label: Linked Issues
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description: Learn how to effectively use linked issues with CodeRabbit for better pull request assessments
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sidebar_position: 6
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---
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# Linked Issues
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CodeRabbit provides intelligent assessment of linked issues to validate whether pull requests properly address their requirements. This guide explains how to effectively use linked issues and write clear issue descriptions for optimal results.
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## Understanding Linked Issues
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A linked issue is one that is explicitly referenced in your pull request description using platform-specific syntax:
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- GitHub: `fixes #123`, `closes #123`, `resolves #123`
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- GitLab: `closes #123`, `fixes #123`, or full URLs
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- Jira/Linear: Full URLs to tickets
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When CodeRabbit detects linked issues, it analyzes them against your pull request changes to determine if the requirements are met:
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![Linked Issue Assessment Example](/img/guides/linked-issue.png)
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## Best Practices for Issue Writing
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### Issue Titles
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Create descriptive, technical titles that clearly state the goal:
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✅ Good Examples:
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- "Add PrismaLint integration to configuration flow"
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- "Fix race condition in user authentication"
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- "Implement caching for GraphQL queries"
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❌ Poor Examples:
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- "Fix bug"
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- "Update code"
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- "Improve performance"
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### Issue Descriptions
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Write comprehensive descriptions that provide clear technical context:
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1. **Problem Statement**
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- Clearly describe what needs to be changed
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- Include technical details about affected components
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- Reference specific files or functions if known
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2. **Expected Solution**
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- Outline the desired implementation approach
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- Include code examples or pseudo-code when relevant
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- List specific acceptance criteria
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Example Description:
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```markdown
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Problem:
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The configuration system doesn't validate Prisma schema files before deployment,
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leading to potential runtime errors.
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Solution:
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Integrate PrismaLint into the configuration flow to:
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- Validate schema files during PR checks
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- Enforce consistent naming conventions
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- Prevent common Prisma anti-patterns
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Affected Components:
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- Configuration validation pipeline
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- CI/CD workflow
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- Schema validation logic
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Acceptance Criteria:
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- [ ] PrismaLint runs on all PR checks
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- [ ] Failed validations block merging
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- [ ] Clear error messages for schema issues
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```
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### Consistent Terminology
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Use consistent terminology between issues and pull requests:
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✅ Good:
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- Use the same technical terms consistently
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- Reference components with their exact names
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- Maintain consistent naming patterns
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❌ Poor:
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- Mixing different terms for the same component
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- Using vague or non-technical language
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- Inconsistent capitalization or formatting
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## Linking Issues Effectively
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### In Pull Requests
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1. **Direct References**
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```markdown
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Fixes #123
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Resolves organization/repo#456
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Closes https://github.com/org/repo/issues/789
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```
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2. **Multiple Issues**
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```markdown
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This PR addresses:
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- Fixes #123
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- Closes #456
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- Resolves https://jira.company.com/browse/PROJ-789
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```
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### Cross-References
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For better traceability:
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1. Add PR references in issue comments
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2. Use complete URLs when linking external systems
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3. Maintain bidirectional links between related issues
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## How CodeRabbit Assesses Linked Issues
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CodeRabbit evaluates linked issues by:
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1. Analyzing issue titles and descriptions
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2. Comparing changes in the pull request
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3. Validating if requirements are met
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4. Providing an assessment with:
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- ✅: If the objective has been addressed in the PR. The 'Explanation' column will be left blank.
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- ❌: If the objective has not been addressed in the PR. Here a brief explanation is added to the 'Explanation' column.
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- ❓: If it is unclear whether the objective has been addressed. Here a brief explanation is added to the 'Explanation' column.
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:::note
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Only the issue title and description are considered in the assessment. Comments and discussion threads are not currently analyzed.
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:::
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## Tips for Better Assessments
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1. **Be Specific**
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- Include clear, measurable objectives
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- List specific technical requirements
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- Reference affected code components
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2. **Provide Context**
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- Explain why changes are needed
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- Document current behavior
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- Describe expected outcomes
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3. **Use Technical Details**
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- Include file paths when known
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- Reference specific functions or classes
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- Mention relevant technologies
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4. **Keep It Focused**
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- One main objective per issue
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- Clear scope boundaries
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- Specific acceptance criteria
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## Related Resources
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- [Review Instructions](./review-instructions.md)
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- [Issue Chat](./issue-chat.md)
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- [Issue Creation](./issue-creation.md)

‎docs/guides/ondemand-reports.md

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title: On-demand Reports
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sidebar_label: On-demand Reports
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description: CodeRabbit offers a way to generate on-demand reports using a simple API request
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```mdx-code-block

‎docs/guides/review-instructions.md

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CodeRabbit offers various customization options to tailor the reviews to your
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specific requirements. Customizations can be made using one of the below
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The guide explains how to add custom review instructions for the entire project.

‎docs/guides/scheduled-reports.md

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title: Scheduled Reports
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sidebar_label: Scheduled Reports
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description: Learn how to set up automated recurring reports with CodeRabbit Pro
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‎docs/integrations/code-graph-analysis.md

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---
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title: Code Graph Analysis
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description: Learn about CodeRabbit's intelligent graph-based code analysis.
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sidebar_label: Code Graph Analysis
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sidebar_position: 6
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---
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# CodeRabbit Code Graph Analysis
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## What is Code Graph Analysis?
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Code Graph Analysis is an intelligent code analysis feature that enhances your code reviews by automatically mapping relationships between files in your codebase. By
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understanding how your code connects and interacts, Code Graph provides concrete snippets of context that makes reviews more effective and insightful.
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## How Code Graph Analysis Enhances Your Reviews
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When reviewing code with CodeRabbit, Code Graph Analysis automatically:
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- **Maps symbol definitions and references** across your entire codebase
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- **Analyzes commit history** to identify files that frequently change together
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- **Builds relationship graphs** showing how different parts of your code connect
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- **Enriches reviews with contextual information** about related code
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Code Graph Analysis is also available in the CodeRabbit Chat. CodeRabbit Chat will automatically analyze your codebase with it when the agent deems it necessary.
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## Key Features
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### Three Types of Contextual Information
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Code Graph Analysis adds three powerful layers of context to your reviews:
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1. **Definition Files**: Files containing definitions that are referenced in the current code
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2. **Reference Files**: Files that reference symbols defined in the current code
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3. **Related Files**: Files that appear related based on usage patterns and commit history
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### Language Support
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Code Graph Analysis works with:
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- Bash
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- C
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- C#
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- C++
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- CSS
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- Elixir
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- Go
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- Java
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- JavaScript
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- Kotlin
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- Lua
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- PHP
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- Python
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- Ruby
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- Rust
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- Scala
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- Swift
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- TSX
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- TypeScript
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## Availability
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Code Graph Analysis is available on the Lite tier and above.
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---
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Learn more about CodeRabbit's advanced features at [coderabbit.ai](https://coderabbit.ai)

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