Please teach copilot about size_of and align_of in rust

[mahkoh]

🏷️ Discussion Type

Bug

💬 Feature/Topic Area

Copilot in GitHub

Body

Every time I have copilot review rust code that uses the size_of and align_of functions, it tells me that my code won't compile. For example: mahkoh/jay#1208 (comment)

But obviously it does compile because those functions are in the prelude. This exact "bug", as copilot calls it, has been a copilot comment probably at least 100 times for me.

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[Lxcardoza993]

You're right — size_of and align_of (like size_of_val, align_of_val) live in std::mem and are re-exported into the standard prelude, so ordinary Rust code compiles with no use statement. The only real cases needing an import or fully-qualified path are crates with #![no_implicit_prelude] (or no_std setups that disable it) and name shadowing. Copilot flagging it ~100 times is a persistent pattern error, not a one-off — but there are ways to stop it:

1. Give Copilot an explicit repo rule. Copilot reads custom instructions from .github/copilot-instructions.md at the repo root; it applies to review comments, chat, and completions:

## Rust rules

- `std::mem::{size_of, align_of, size_of_val, align_of_val}` are **prelude items**.
- They need `use std::mem::...` ONLY when the crate has `#![no_implicit_prelude]`.
- Do not flag them as "cannot find function" or suggest importing them in normal crates.
- These compile as-is: `size_of::<T>()`, `align_of::<T>()`, `size_of_val(&value)`.

2. Workspace-level fallback. If a PR review happens where the instruction file isn't picked up (or your toolchain skips it), put the same rules into the workspace-level instructions (Copilot settings → Instructions in VS Code). The two scopes together cover repo review and local chat.

3. Use the 👎 on the review comment. "Don't flag prelude functions" feedback does feed back into the model quality loop — with the instruction file and consistent downvotes, this class of false positive usually drops to near zero.

Also: linking your PRs as examples here (100+ false positives across public PRs is a far more actionable review-quality signal than "review is wrong") is worth doing — GitHub staff route these.

If this nails it, marking it as the accepted answer would be appreciated. 🦀