Code review that knows your rules.

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What is it?

Revvy is a VS Code extension that brings structured, AI-powered code review directly into your editor. Instead of generic AI feedback, it enforces a set of rules you define in YAML — tailored to your team's standards, domain, or industry requirements (e.g. safety-critical embedded C/C++, Python, and more).

Why not just use /review or type a prompt?

• Many developers are not good at writing prompts.
• Every review requires crafting a new prompt tailored to a specific tech stack or language.
• AI can't deliver a thorough review without specific rules or best practices — the kind that are usually defined at the company or team level.
• Rules vary from one developer to another, which is why Revvy uses hardcoded, shared rules stored in a single YAML file that the whole team uses.
• A clean UI that shows you the exact line of code with an inline comment when an issue or warning is detected.

That's all?

Not quite. Revvy also:

• Reviews multiple GitHub PRs and GitLab MRs in a single pass using MCP
• Validates your code against Jira ticket requirements — so nothing slips out of scope
• Generates integration tests (functional + regression)
• Provides a Copy as Markdown button that copies all review comments along with a ready-to-use prompt — paste it into your favorite AI assistant (ChatGPT, Claude, Copilot, etc.) to fix every issue in one shot
• (Coming soon) Auto-comment on PRs/MRs — Revvy posts a comment on the pull/merge request stating it has been reviewed by the tool, with a summary of findings for reviewers and maintainers to see at a glance

It works with the AI backend you already have — GitHub Copilot (no extra key needed), OpenAI GPT-4o, or Anthropic Claude — with automatic fallback.

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Why Revvy over other tools?

	Revvy	Generic AI prompt (Copilot Chat, etc.)	Paid review tools
Rule-driven, team-shared standards	Yes — YAML profiles in your repo	No — prompt varies per developer	Partial — cloud-managed rules
Works with your existing AI subscription	Yes — Copilot, OpenAI, Anthropic	Yes	No — separate subscription
Embedded / safety-critical profiles	Yes — C/C++, Yocto, MISRA-style rules	No	No
Multi-repo PR/MR in one pass	Yes — GitHub + GitLab via MCP	No	Partial
Cost	Free & open-source	Included in your AI plan	Paid

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Demo

Quick Start

From the VS Code Marketplace:

Search for Revvy in the VS Code Extensions panel and install it.

From source:

git clone https://github.com/YonK0/revvy.git
cd revvy
npm install
npm run compile
# Press F5 in VS Code to launch the Extension Development Host

Once installed, click the Revvy icon in the Activity Bar. Three example profiles are created automatically on first use (c-embedded, yocto, python).

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Writing Rule Profiles

Create .yaml files in .vscode-reviewer/profiles/. Rules are reloaded automatically on save.

profile:
  id: my-team
  label: "My Team Rules"
  version: "1.0.0"
  file_patterns:
    - "**/*.ts"

  rules:
    - id: NO_CONSOLE_LOG
      title: "No console.log in production code"
      category: "coding-standards"
      severity: warning      # error | warning | info
      enabled: true
      description: |
        console.log statements should not be merged to main.
        Use a structured logger instead.

See the bundled profiles in .vscode-reviewer/profiles/ for full examples.

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MCP Servers (Optional)

Enables Jira ticket fetching and multi-repo PR/MR review. Copy .vscode/mcp.json and fill in your credentials — tokens are prompted at runtime and never stored on disk.

Server	Install	Used for
GitHub	Docker	Fetch PR diffs for multi-repo review
GitLab	npm i -g @modelcontextprotocol/server-gitlab	Fetch MR diffs
Atlassian	pip install mcp-atlassian	Fetch Jira ticket requirements

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Requirements

• VS Code 1.96.0+
• Git in PATH
• One of: GitHub Copilot subscription or free tier / OpenAI API key / Anthropic API key

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Architecture

src/
├── extension.ts      # Entry point — commands, WebView provider, YAML watcher
├── panelProvider.ts  # WebView UI — welcome, loading, results screens
├── reviewer.ts       # Core engine — prompt construction, AI call, response parsing
├── aiBackend.ts      # AI abstraction — Copilot, OpenAI, Anthropic + fallback chain
└── ruleLoader.ts     # YAML loader — file scanning, parsing, live-reload watcher

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Contributing

Contributions are welcome — new rule profiles, AI backends, bug fixes, UI improvements. See CONTRIBUTING.md.

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