Okay, I have to ask because I just spent like an hour playing with this and my results were... mixed.
I was cleaning up an old HubSpot email workflow module script—you know the type, spaghetti code from 2018—and I highlighted a block that was doing some weird date formatting. I right-clicked, hit "Ask Cursor to Fix," and typed "make this more readable and use dayjs."
The first attempt was actually pretty good! It swapped out the vanilla JS date mess for clean dayjs calls. But then I tried it on a more complex function that had a mix of logic and API calls, asking it to "add error handling," and it kinda went off the rails. It added try-catches but also rewrote parts that were already working fine.
My quick takeaways:
* For simple, scoped syntax swaps or linting fixes? **Works great.**
* For understanding *business logic* intent? **Hit or miss.** You really have to be super specific.
* It feels faster than opening the chat and pasting the code, which I like.
Has anyone else put this through its paces? I'm curious:
* What kind of "fixes" have you asked for that actually worked well?
* Any tips on phrasing the request to get better results?
* Found a particular type of task where this feature is a total time-saver?
I want to believe this can be a staple in my workflow, but I need more data points!
~ jenny
Automate the boring stuff.
Totally get the mixed results! Your point about it being super fast is spot on - that's the killer feature for me too, even when the output needs tweaking.
I've had the best luck with super granular requests. Instead of "add error handling," I'll go with something like "wrap the fetch call in a try-catch and log errors to the console without breaking the loop." It still sometimes gets creative with the surrounding code, but less often.
For me, it's amazing for stuff like:
* Converting promise chains to async/await (or vice versa)
* Rewriting a gnarly ternary into an if/else for readability
* Adding JSDoc comments when I paste in a function signature from somewhere else
It's like having a really eager intern. Great for the tedious bits, but you gotta give them exact instructions 😅
Yeah, the "really eager intern" comparison is perfect. That speed for tedious conversions is exactly what makes it stick for me, even when it needs supervision.
I find it starts to wobble when the task isn't purely syntactical. For instance, asking it to "convert this chain of `WHERE` clauses into a `CASE` statement" might give you valid SQL, but the logic could be subtly wrong if the original conditions were order-dependent. You still need to be the one who knows the data flow.
Your tip about granularity is key. It's less "fix this function" and more "swap these two parameters" or "add a null check for this column." The more you treat it like a very precise command line, the better it behaves.
Exactly - that need for you to know the data flow is the crucial line. It's a pattern-matching tool, not a logic-understanding one.
Your SQL example is spot on. I've seen similar things in API response handling, where it'll restructure a function perfectly but miss that one field could be null from a specific endpoint. It can't infer context we haven't told it.
So maybe the trick is to frame it as "translate this exact intent" rather than "understand and fix the problem." It's the difference between giving a command and delegating a task.
Raise the signal, lower the noise.