CodeRabbit

Helps teams catch issues, understand changes, and validate code before merge across pull requests and coding workflows.

Helps teams focus review attention on valuable, urgent, or risky pull requests and move work through the queue efficiently.

Understand code changes in detail so reviewers can assess their impact and make informed decisions before shipping.

Finds and verifies real security risks across code changes and repositories, helping teams prioritize and fix vulnerabilities before they are exploited.

Resolve engineering work with connected context and a collaborative Slack agent, while keeping workflows governed and costs tied to active agent time.

Align teams on codebase-informed plans and give coding agents clearer context, helping reduce rework before code is written.

CodeRabbit Review

CodeRabbit Review provides automated, context-aware code reviews for pull requests and changes made in IDEs, the CLI, and coding-agent workflows. It inspects changes for correctness, test coverage, security and policy risks, and incomplete work, using repository context and team guidance. Reviews include plain-language summaries and walkthroughs, while the workflow can provide sandbox evidence, learn from team corrections, support coding-agent fix loops, apply suggested changes, and automate checks and follow-up tasks. IDE and CLI reviews support staged and unstaged changes before a pull request, with inline feedback and coding-agent handoffs.

• Review Changes Automatically
  Get an independent first pass on changes and identify issues before a human review or merge.
• Review Changes Before Pull Requests
  Get feedback on staged and unstaged changes in the terminal or editor before raising a pull request.
• Ground Reviews In Codebase Context
  Reviews consider repository structure and relevant project context rather than assessing only changed lines.
• Catch Defects And Test Gaps
  Calls attention to potential correctness problems, edge cases, and test coverage gaps for teams to investigate before merge.
• Flag Security And Policy Risks
  Surfaces security and policy concerns while changes are still in the pull request workflow.
• Validate Changes Independently
  Separates the review layer from the system that wrote the code, providing an independent assessment of developer and coding-agent changes.
• Review Across Development Workflows
  Review changes in an IDE or CLI while context is fresh, continue in coding-agent workflows, and review complete pull requests in a Git provider.
• Hand Off Review Context To Agents
  Connect reviews to supported coding agents and provide recommended changes with context for generate-review-iterate workflows.
• Spot Incomplete And Inconsistent Changes
  Highlights incomplete work and inconsistencies for teams to evaluate before accepting a change.
• Understand Pull Requests Faster
  Summaries and walkthroughs help reviewers understand what changed and evaluate the pull request with relevant context.
• Add Evidence To Suspected Findings
  Sandbox reproduction provides additional evidence about selected suspected failure modes for reviewers to consider.
• Apply Team Standards Across Reviews
  Approved corrections and team standards can inform future reviews and help maintain consistency across changes.
• Review Fixes Before Human Review
  Repeated review and fix cycles help teams check coding-agent changes while work is still in progress.
• Apply Suggested Fixes Quickly
  Developers can act on findings by applying a suggested patch directly or opening a reviewed follow-up pull request.
• Enforce Quality Gates Before Merge
  Verifies requirements such as passing tests, required approvals, security policies, and organization-specific checks before merging.
• Start Reviewing Without A Subscription
  Use IDE reviews through the VS Code plugin without a subscription, with paid plans available for higher rate limits and full context-aware reviews.
• Complete Routine Pull Request Work
  Automates selected finishing tasks around a change so developers can address routine follow-up work within the review workflow.
• Automate Post-Merge Follow-Up
  Configurable tasks after a pull request merges reduce the need for separate manual handoffs.
• Review Code Across Languages
  Use IDE code reviews across a broad range of commonly used programming languages.

CodeRabbit Triage

CodeRabbit Triage turns a growing pull request stream into an ordered, actionable queue. It scores and ranks PRs by value, impact, urgency, risk, and review effort, and surfaces stale PRs and work that may be closed. Teams can use a cross-repository Kanban queue with custom filters and saved views, route PRs to suitable reviewers, and review, repair, reassign, merge, close, or follow PRs from the queue. Slack features include scheduled queue digests, reviewer requests, and the ability to approve or close a PR. Advanced and Enterprise plans include security-informed prioritization.

• Prioritize High-Value And Risky PRs
  See value, impact, urgency, risk, and review effort together to focus attention on important work and decide which changes need closer review.
• Identify PRs That Need Attention
  Use risk, effort, impact, and staleness signals to determine which PRs warrant a closer look and which may be candidates for closure.
• Organize PRs In One Queue
  Review open PRs across repositories in a single view, with filters and saved views to make the queue easier to navigate.
• Route PRs To Suitable Reviewers
  Match PRs with appropriate reviewers and assign them from the triage workflow to help move review forward.
• Act On PRs From The Queue
  Handle key pull request actions in the Triage queue, including review, repair, reassignment, merging, closing, and following a PR.
• Spot Duplicate PR Work
  Identify duplicate work in the PR queue so teams can account for overlapping contributions when deciding what to review.
• Manage PR Triage In Slack
  Receive a scheduled view of the queue, request reviewers, and approve or close PRs through Slack.

CodeRabbit Explain

CodeRabbit Explain helps teams understand and assess code changes in detail. Its Change Stack workspace makes pull requests structured and navigable, while semantic diffs explain code edits, movement, and functional changes. Reviewers can inspect findings, ask questions about changes, files, and code, and—on eligible plans—see a pull request’s blast radius and architecture impact. CodeRabbit Explain also documents changes to help reviewers judge code before it ships.

• Understand Every Change
  Get detailed explanations and documentation of changes so reviewers can better understand the code before it ships.
• Navigate Changes In One Workspace
  Review a pull request in a structured workspace designed for navigating its contents, asking questions, and taking action.
• See What Changed And How
  Understand the structure of a change through explanations of exact edits, moved code, and changes in functionality.
• Assess Findings And Fix Priorities
  Inspect findings from a change, assess its readiness to merge, and determine which issues to address first.
• Map Downstream Change Impact
  See the downstream reach and impact of a pull request beyond the lines it directly modifies. This capability is listed for Advanced and Enterprise plans.
• Understand System-Level Impacts
  Review how a pull request changes system-level responsibilities and relationships. This capability is listed for Advanced and Enterprise plans.
• Ask Questions About Code Changes
  Ask questions about a pull request’s changes, individual files, or code to clarify what you are reviewing.
• Request Further Analysis Or Changes
  Trigger the cloud-based CodeRabbit AI Engineer from the Explain workflow for additional analysis or to execute changes for you.

CodeRabbit Secure

CodeRabbit Secure uses security-focused agents and semantic analysis to identify vulnerabilities and exposed secrets in pull requests, committed code, and infrastructure configuration. It traces potential attack paths across code and linked repositories, assesses reachability and exploitability, and verifies findings before they reach teams. Deep Scans can run on demand or on a schedule, while ongoing reviews and delta scans keep coverage connected to code changes. For eligible findings, CodeRabbit can provide reviewable fixes, verify fixes after merge, and support runtime testing in a prepared environment. Repository administrators can also enforce merge checks for open critical findings.

• Trace Exploitable Paths Across Code
  Investigates how vulnerabilities may flow across files, services, and trust boundaries to surface risks that depend on understanding how the code works.
• Scan Committed Code And Infrastructure
  Examines the repository beyond its latest pull request to establish a security baseline and identify risks in code that may have shipped earlier.
• Verify Findings Before They Reach You
  Provides evidence-based findings and checks whether an issue can be reached and exploited, helping teams focus on risks supported by the code.
• Review Security Risks Before Merge
  Checks incoming changes for security issues and presents findings in the pull request, where teams can evaluate them as part of their review workflow.
• Keep Security Coverage Current
  Combines ongoing pull request reviews with scans of changed or stale areas so security coverage can keep pace with the codebase.
• Test Findings In A Prepared Environment
  Helps teams examine whether a suspected vulnerability reproduces under tested conditions, with the test plan, execution details, and evidence available alongside the outcome.
• Block Merges On Critical Findings
  Enforces a security gate on pull requests so configured findings continue to block merging until CodeRabbit verifies the fix.
• Draft Reviewable Vulnerability Fixes
  Turns eligible findings into proposed code changes for developers to inspect, adapt, and approve through the pull request workflow.
• Trace Risks Across Linked Repositories
  Adds context from connected repositories when a request crosses repository boundaries, helping distinguish real attack paths from risks addressed by safeguards elsewhere.
• Track Verified And Stale Areas
  Shows which parts of a repository have current security verification and where changes have made earlier coverage stale.
• Verify Fixes And Resolve Findings
  Confirms whether a finding remains present and automatically resolves it after CodeRabbit verifies a merged fix.
• Track Findings Across The Organization
  Gives engineering and security leaders an organization-wide view of security review findings, their resolution, and areas where risk is accumulating.
• Assess Security Impact Beyond Changed Lines
  Shows how a pull request may affect security-relevant paths and system relationships beyond the lines directly changed.
• Control Deep Scan Spending
  Lets teams set scan spending limits and resume an unfinished scan without starting over, helping make security scanning costs predictable.
• Route Findings Into Existing Tools
  Connects security findings with Jira and Linear workflows and makes Deep Scan findings available through an API.
• Complement Existing Security Scanners
  Adds reasoning about first-party application logic and code context while teams continue using the security tools already in their stack.

CodeRabbit Engineer

CodeRabbit Engineer is an AI collaborator for Slack that brings together context from code repositories, tickets, documentation, monitoring systems, cloud platforms, and team conversations. It answers questions, investigates issues, performs engineering tasks, opens pull requests, and creates work artifacts in connected tools. Teams can collaborate with the agent in shared threads, while channel- and user-scoped controls govern access, knowledge, integrations, and spend.

• Bring Context Together
  Give the agent access to relevant code, tickets, documents, monitoring, cloud systems, and team conversations so it can reason about work with organizational context.
• Move Engineering Tasks Forward
  Use the agent to investigate incidents, identify causes, make targeted code changes, open pull requests, and create follow-up artifacts in connected tools.
• Guide Work In Shared Threads
  Keep the team involved where work is already happening by guiding the agent, adding context, changing direction, and resuming tasks in shared Slack threads.
• Carry Team Knowledge Forward
  Make decisions, fixes, conventions, and runbooks available as continuing context across teams, channels, and tasks.
• Control Access And Costs
  Set channel- and user-scoped permissions, decide which tools are available, and review agent activity and costs with run-level attribution.
• Automate Recurring Updates
  Deliver scheduled or signal-triggered summaries and workflow outputs in Slack without requiring the team to chase them.
• Pay For Active Agent Time
  Base usage charges on active agent minutes, with runs metered by the second and totaled across the team for the billing period.
• Customize Agent Workflows
  Add skill files and custom sandboxes to shape how the agent works for your team.

CodeRabbit Plan

CodeRabbit Plan turns a text idea or issue-tracker ticket into an editable, phased coding plan grounded in relevant codebase context. Teams can define scope, assumptions, and success criteria, review and refine the plan collaboratively, then hand its context-rich prompt to a coding agent or export it to Cursor, VS Code, or Windsurf. Plan generation can be configured with rules based on labels, projects, assignees, or custom criteria.

• Ground Plans In Relevant Codebase Context
  Give teams a plan informed by codebase research, including relevant files, patterns, dependencies, and the proposed changes.
• Align On The Approach Before Coding
  Review and refine the plan together so the team can align on the approach before handing work to a coding agent.
• Hand Off Plans To Your Agent Of Choice
  Pass a context-rich prompt to the coding agent or tool the team chooses, without being tied to a single provider.
• Start Planning From Ideas Or Tickets
  Turn a written idea or an existing issue-tracker ticket into the starting point for a coding plan.
• Set Rules For When Plans Are Generated
  Apply plan-generation rules to match the team's workflow, such as generating plans for selected labels, projects, or assignees.