Your AI agent wishes it was this good.
Scrubby is an AI-powered platform that learns what your codebase is about, how domains are connected, and how your team actually builds within it.
This knowledge powers everything from real-time code review and automated PR analysis to on-demand architectural queries and new developer onboarding.
Scrubby runs in any AI-powered editor. Automated PR reviews via the GitHub App work independently of editor choice. No platform lock-in.
Scrubby handles convention enforcement and co-change analysis automatically, so reviewers can focus on logic and architecture. Review cycles compress and merge velocity increases.
Scrubby catches bugs that often slip through file-level review, such as auth changes with implications for your API or data layer changes that affect caching. This means less downtime for your app and a more stable product for your users.
Scrubby gives AI agents the exact context they need upfront, eliminating wasted exploration and slashing token spend on every request. The result is dramatically lower API bills and noticeably faster agent responses.
Scrubby ensures your favorite AI tools' output meets your actual conventions and architectural patterns, so AI-generated code gets the same scrutiny as human-written code.
No. Linters enforce universal, pre-defined rules that are the same for every codebase. Scrubby learns the conventions, architectural domains, and co-change patterns specific to your repository by analyzing your code and git history. The two serve different purposes and work well together.
Scrubby's intelligence is pre-computed. When you request context or a review, the knowledge is already structured and ready. There's no waiting for a full codebase scan. For GitHub PR reviews, analysis runs in parallel and results appear as inline annotations.
Claude Code, Cursor, Windsurf, VS Code, Zed, and any other AI-powered editor. Scrubby also integrates as a GitHub App for automated PR reviews that work independently of your editor choice.
Scrubby stores file metadata, AI-generated summaries, and architectural metrics — not your full source code. Clipped file contents are sent to our servers during indexing and analysis, processed through the Anthropic API, and discarded after summaries are generated. Only the summaries persist.
Point Scrubby at your repository and the initial index runs in minutes. After that, only changed files are re-processed. Domain discovery and convention extraction happen automatically with no manual configuration.
Yes. Scrubby identifies cohesive structural clusters within your dependency graph regardless of repository size or organization. Monorepos with multiple services, shared libraries, and feature modules are handled naturally.
JavaScript, TypeScript, Python, Ruby, Go, and Java, with framework-specific intelligence for React, Next.js, Rails, Django, and more. Language and framework detection is automatic.
