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Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.
AI code review tool with huge adoption; ~870K visits and 1.4M saves.
Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.
Turns Git commits and PRs into AI-summarized daily or weekly reports delivered to Slack or email, no source access.
Free open-source VS Code fork letting developers connect directly to any AI model without a proxy, for privacy-focused coders.
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
- ✦AI code completion and suggestions
- ✦Natural-language code generation
- ✦In-IDE chat assistance
- ✦AI code review
- ✦IDE integrations (VS Code, JetBrains, etc.)
- ✦GitHub integration
- ✦AI-powered code reviews
- ✦Contextual line-by-line feedback
- ✦Critical change flagging
- ✦Bot interaction
- ✦Direct commit from GitHub
- ✦Integration with Jira & Linear
- ✦Agentic Chat with CodeRabbit
- ✦Product analytics dashboards
- ✦Customizable reports
- ✦Docstrings generation
- ✦Natural-language to Git command suggestions
- ✦AI-driven command matching
- ✦Copy-ready command output
- ✦Git guides and reference
- ✦AI-summarized commit and PR reports
- ✦Daily and weekly scheduled digests
- ✦Slack and email delivery
- ✦One-click OAuth or webhook setup
- ✦GitHub, GitLab and Bitbucket support
- ✦Templates for standups and reports
- ✦Tab-key autocomplete suggestions
- ✦Inline quick-edit on selected code
- ✦Chat with agent, gather, and normal modes
- ✦Direct connections to any LLM provider, no proxy backend
- ✦One-click import of VS Code themes and settings
- ✦Checkpoints to track and revert LLM-made changes
- ✦Lint error detection
- ✦Fast apply designed for large, 1000+ line files
- →Speeding up coding with AI completions
- →Generating code from plain-language prompts
- →Getting in-editor help and explanations
- →Reviewing pull requests with AI
- →Understanding unfamiliar codebases
- →Automated code review for pull requests
- →Identifying potential bugs and vulnerabilities
- →Improving code quality and consistency
- →Onboarding new developers with AI-driven guidance
- →Find the correct Git command quickly
- →Learn Git syntax by describing a goal
- →Avoid memorizing Git flags
- →Keep stakeholders updated on what shipped
- →Replace manual status updates and standups
- →Give teams visibility into Git activity
- →Switching from Cursor or Windsurf while keeping data private
- →Running local open models like DeepSeek or Llama instead of paying per API call
- →Connecting directly to frontier models such as Claude or Gemini
- →Editing and refactoring large codebases with AI help