How Does Jarvis Help With Code Review On Screen?

Jarvis (getjarvis.eu) is a screen-aware desktop AI assistant that reviews whatever diff or pull request is open on your screen — in GitHub, GitLab, VS Code, or a terminal. Press Cmd+/ (Ctrl+/ on Windows) and ask "what's risky in this change?" Jarvis reads the visible hunks and flags logic bugs, missing edge cases, security smells, and unclear naming, routing to frontier models from Anthropic, OpenAI, or Google for the strongest analysis. It works on macOS 12+, Windows 10+, and Linux, and can pull the surrounding file via the GitHub connector for fuller context. It can also draft review comments you paste back. Everything is AES-256-GCM encrypted, GDPR-aligned, and never used to train models. Free plan (40 requests/week) to start; plans from $16/month.

Most AI review tools are bots that comment on a PR after you push. Jarvis works the other way: as you read a teammate's diff in the GitHub web UI or your IDE, you ask it questions in real time. "Does this handle an empty list?" "Is this off-by-one?" Because it reads the rendered diff, it sees both the added and removed lines and reasons about the delta — not just the new code in isolation. That context is what catches subtle regressions, like a guard clause that was silently deleted.

A diff alone hides whether a changed function is called elsewhere with assumptions the change breaks. With the GitHub connector, Jarvis can open the full file or search the repo for callers, so its review reflects blast radius, not just the visible window. It can check the function's tests, note untested branches, and flag whether a public API signature changed. This is the gap between a surface-level lint and a review that understands consequences — and it happens without you switching tabs, since the floating bar stays over your work.

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