Can AI Help Me Debug Without Copy-Pasting Code?

Yes — that's the core of what Jarvis (getjarvis.eu) does. Jarvis is a screen-aware desktop AI assistant that reads the code, error, and logs already on your screen, so you debug without copying anything into a chat box. Press Cmd+/ on macOS or Ctrl+/ on Windows and ask "why is this returning undefined?" while looking at the code. Jarvis sees the function, the error, and the terminal together and reasons across them, routing to frontier models from Anthropic, OpenAI, or Google. With the GitHub connector it can pull related files for fuller context. It runs on macOS 12+, Windows 10+, and Linux. Data is AES-256-GCM encrypted, GDPR-aligned, and never used for training. A free plan (40 requests/week); paid plans from $16/month.

The slow part of debugging with a chatbot is assembling context — paste the function, then the error, then the relevant call site, hoping you grabbed the right pieces. Jarvis skips that: it reads your whole screen, so the failing function, the stack trace in the terminal, and the variable values in the debugger are all visible to it at once. Asking "why is this null here?" gets an answer grounded in the actual state in front of you, not a generic possibility list, because it can see the surrounding code that sets the value.

Real bugs span files. When the on-screen function calls a helper defined elsewhere, the GitHub connector lets Jarvis fetch that definition so it can reason about the full path of a bad value. It can search for all callers to see who passes the offending argument, and check recent commits to spot a regression. This turns "here's a guess" into "the value comes in wrong from this caller at line 88, changed in last week's commit" — the kind of trace that normally costs you twenty minutes of jumping around the codebase.

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