Timestamp queries will give you essentially time spans you can use for profiling, but anything more than that and you really want to use a dedicated tool from your vendor like NSight, RGP, IGA, XCode, or PIX.

> Right now I feel like the only way to write efficient WebGPU code is to deeply understand specific GPU architectures. I hope some day there's a dev tools tab that shows me I'm spending too much time sampling a texture or there's a lot of contention on my atomic add.

It's kind of the nature of the beast. Something that's cheap on one GPU might be more expensive on another, or might be fine because you can hide the latency even if it's slow, or the CPU overhead negates any GPU wins, etc. The APIs that give you the data for what you're asking are also vendor-specific.

That's fine—same with CPUs, right? But if I do something that's slow on _my_ CPU, at least there's tooling that will show me!

I know that the reason is a lot of technical complexity (plus little standardization between vendors), but I think the end goal should be to make GPU programming more accessible.