If you opened this article, you probably already agree with me: sometimes TypeScript compiles painfully slowly.

The same thing happened to @_chenglou — an amazing dev who inspires me (he worked on React, Messenger, ReasonML and ReScript, and currently Midjourney, Pretext).

He's also a user of Sury — the fastest schema validation library, which I maintain — and the author of this issue: "Large TS types cause type inference slowdown".

That's... not nice. But I knew ArkType exists, and that people have built wild things in TS's type system (Doom included). So the slowness was clearly solvable, not fundamental. Here's the recipe I used. You can apply it to your own library.

Before we begin, here are the results. These are type-instantiation counts, measured with @ark/attest:

The title comes from that 15.7× on S.Output. Extraction is the operation you hit most often: every type X = S.Output<typeof schema> in your code pays for it.

Let's begin. The recipe is three steps.

1. Pin it down first

If you want to change something, you first need a way to know you didn't break it. For a library like this, that means tests for types:

import { expectTypeOf } from "vitest";
import * as S from "sury";

const user = S.schema({ id: S.string, age: S.number });

// Pin the inferred type. If it drifts, the test fails.
expectTypeOf<S.Output<typeof user>>().toEqualTypeOf<{
  id: string;
  age: number;
}>();

I used to use ts-expect for this, but I migrated to Vitest's type-testing utils (expectTypeOf, above) to drop a dependency. Either way, I already had the tests, and I'll admit they really earned their keep. A type optimization can quietly turn { a: string } into { a?: string } and nothing throws. The tests are what catch that.

2. Measure before you touch anything

If you want to improve something, you have to measure it first, or you can't actually tell whether you improved anything.

For this I used Attest (@ark/attest) from the ArkType creators. I'm very inspired by their TS skills, and I'll admit I'm not that strong at type-level optimization myself. Good thing I have other strong parts. 😄

It counts the type instantiations an expression costs and pins them as a baseline:

import { bench } from "@ark/attest";
import * as S from "sury";

bench("define a user schema", () => {
  return S.schema({ id: S.string, age: S.number });
}).types([230, "instantiations"]);

Bonus: bake those baselines into CI, and any future regression will fail the build.

3. Let Claude do the heavy lifting

The third step was the easy one: I asked Claude to find the most impactful type-instantiation optimizations.

The fix turned out to be small. To read a schema's type back out, S.Output / S.Input matched against the entire Schema<…> type. That type is huge: a big object with several with overloads, intersected with a union of every schema variant. So TypeScript had to expand all of it on every extraction, and the cost grew with the schema:

// Before: match the whole Schema<…> shape just to read Output back out
type Output<T> = T extends Schema<infer Output, unknown> ? Output : never;

But every Sury schema already carries a ~standard field (the Standard Schema marker) that holds the resolved types. So the fix is to read that one slot directly, instead of re-deriving it from the whole shape:

// After: match only the one field that already holds the type
type Output<T> = T extends { "~standard": { types?: { output: infer Output } } }
  ? Output
  : never;

Now extraction costs the same no matter how big the schema is. That one change is most of the 11–16× you see above.

Do you even need it?

It depends (my favorite answer). But feedback loop speed matters more and more as AI iterates on your code. If your codebase's TS compilation is slow, you can use the same approach to identify the slow parts and optimize them.

Wrapping up

One caveat: 15.7× is the drop in type instantiations, not seconds. I didn't time the actual compile. But instantiations are the work tsc does while type-checking, so fewer of them is a fair proxy for what you feel in the editor. 🙂

Hope this was useful. Check out Sury — the most powerful schema library in the TS ecosystem. Follow me on X at @dzakh_dev, and ask your questions in the comments!