Coding Interview Helper

For the coding problem on screen, and the conversation around it.

Updated 2026-07-31

SyntaxCue is a coding interview helper for live technical interviews — the problem on screen, and the conversation around it. It listens to the interview, transcribes locally, and shows you an AI-generated suggestion using your own OpenAI or Anthropic key. It handles both sides of a coding round: the actual problem on your screen, and the back-and-forth — “what’s the time complexity?”, “how would you handle duplicates?”, “why that data structure?”

How it handles a coding problem

Getting the problem in front of the model. When there’s a coding problem on screen — a LeetCode-style prompt, an editor, a shared doc — you send it to the model with an explicit screenshot. Three ways, all routed through your operating system’s own screenshot tool:

  1. Click “📷 Add screenshot” and drag-select the problem or editor area. It drops into the hint window automatically.
  2. Press the region-screenshot hotkey (optional, off by default, enabled in Advanced settings) to do the same thing without touching the mouse.
  3. Screenshot with your OS’s own shortcut and paste it in (⌘V / Ctrl+V) once you’re listening.

Each of these is a deliberate, one-time capture — the same posture as pasting an image into any chat app. One thing that matters here: a screenshot only works if you’ve configured a vision-capable model in the model field, since answering an image requires it. That’s your own choice, via the free-text model setting.

The verbal side works the same as the rest of the product. System audio is transcribed locally with whisper.cpp, and the model answers from that transcript. So when the interviewer explains a problem out loud, asks a follow-up, or steers the discussion, that conversation is covered too — not just the code visible on screen. A coding round is as much “talk me through your reasoning” as it is the code itself.

It writes in your stack, not just Python. SyntaxCue has a preferred language/framework setting you fill in at setup — type “Go”, “Python/Django”, “TypeScript/React”, whatever you’re interviewing in — and code answers use that instead of defaulting to Python.

Answer style is tunable. A Short / Balanced / Detailed setting controls how much you get back. Live coding rounds often want terser hints than a system-design discussion does — dial it to Short for a direct suggestion in seconds, not a wall of explanation.

What it’s not

Being precise here, because vague claims help no one:

Does it work with LeetCode-style problems?

Yes. Any coding problem visible on your screen — LeetCode, HackerRank, a shared editor, a doc — you capture with a screenshot (button, hotkey, or paste) and the model reads it. There's no platform integration; it just reads what's on screen, which is why it works across all of them.

Do I need to use a specific programming language?

No. There's a free-text language/framework field you fill in yourself — type whatever you're interviewing in, and code answers use it. It only defaults to Python if you don't tell it otherwise; there's no fixed list of "supported" languages.

Does it work for verbal questions, or only code on screen?

Both. Alongside screenshots, it transcribes the interview audio locally, so spoken problems and follow-up questions ("what's the complexity here?", "how would you optimize this?") are handled the same way as the rest of the product.

Do I need a particular model?

For screenshots, you need a vision-capable model, since answering an image requires it — you set the model yourself in a free-text field. For purely verbal questions, any model your key supports works.

For the full setup walkthrough, see Setup. For the system-design side of technical interviews, see the System Design Interview Cheat Sheet. For pricing — a one-time $79 after a free tier of ~10-15 hints, bring-your-own-key with no markup, macOS and Windows — see Pricing.