How to Send Code Snippets and Error Screenshots to ChatGPT or Claude

Debugging with AI is fast — but only if you can deliver the right context. Most developers lose time assembling that context: copy error, switch tab, paste, go back, copy code, switch tab, paste again. Here is how to do it in one step.

What a proper AI debug context looks like

When you ask ChatGPT or Claude to help you debug something, the best results come when you give them full context. Not just the error message — the whole picture:

• A screenshot of the error (the UI or console output)
• The relevant code snippet that is failing
• The stack trace or error text
• A link to the relevant documentation, if applicable

When you give all of that at once, the AI can reason about the full problem instead of asking follow-up questions. It is the difference between a useful first answer and a three-round conversation to get there.

The old way: slow and fragmented

Without a tool like CacheTray, the process looks like this:

1. Screenshot the error in the browser → saved to Downloads
2. Copy the code snippet from your editor
3. Switch to ChatGPT tab
4. Upload the screenshot via the file picker
5. Paste the code snippet
6. Go back and copy the stack trace
7. Switch back to ChatGPT, paste the stack trace
8. Go find the docs URL, copy it
9. Paste it into ChatGPT
10. Write your question and send

That is ten steps for what should be one action.

The CacheTray way

Here is how the same workflow looks with CacheTray installed:

Five steps instead of ten, and they are non-sequential — you collect items in any order, from any tab, without switching to the AI tool until you are ready.

What your tray looks like during a debugging session

CacheTray · debug session

IMG

checkout-error-500.png

CODE

const res = await stripe.charges.create(params)

CODE

Error: No such customer: 'cus_abc123'

LINK

docs.stripe.com/api/errors/handling

Everything you need is right there, labeled, ready to select and send. No file picking, no tab switching, no losing your place in the code.

Works across your whole browser session

CacheTray runs in the background while you work. You do not have to think about it — items accumulate automatically as you copy things. When you are ready to ask ChatGPT or Claude, everything you collected during the session is waiting in the tray.

Items stay in the tray for 3 days by default, so if you are working across a multi-day bug investigation, your collected context is still there the next day. Star items to keep them permanently.

Works with both ChatGPT and Claude

Whether you prefer Claude's extended reasoning or ChatGPT's code interpreter, CacheTray injects into both. Select your items once, then choose which AI to send to. You can even send to both and compare.