
Rust Review
- 5 installs
- 9.5k repo stars
- Updated August 4, 2026
- replicate/cog
Helps with ai & agent building tasks.
About
rust-review is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.
- rust-review
- AI & Agent Building
- AI-coding skill
Rust Review by the numbers
- 5 all-time installs (skills.sh)
- Ranked #13,065 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 5 |
|---|---|
| repo stars | ★ 9.5k |
| Last updated | August 4, 2026 |
| Repository | replicate/cog ↗ |
What it does
Helps with ai & agent building tasks.
Files
Rust review guidelines
This project uses Rust for Coglet (crates/), the prediction server that runs inside Cog containers. It handles HTTP requests, worker process management, and prediction execution.
What linters already catch (skip these)
clippy runs in CI. cargo-deny audits dependencies for license/advisory issues. Don't flag issues these would catch.
What to look for
Error handling
- Use
thiserrorfor typed errors in library code,anyhowfor application errors - Don't use
.unwrap()or.expect()in non-test code unless the invariant is documented - Error context: use
.context()or.with_context()from anyhow, not bare?
Ownership and lifetimes
- Unnecessary cloning where a borrow would work
- Lifetime issues that suggest a design problem (not just annotation noise)
- Arc/Mutex when simpler patterns exist
Async (tokio)
- Blocking operations inside async contexts (use
spawn_blocking) - Missing
.awaiton futures (compiler catches some, but not all logical issues) - Proper cancellation handling and cleanup
- Task/JoinHandle leaks
Safety
- Any
unsafeblock needs justification and a safety comment - FFI boundaries with Python (PyO3) -- check for panics across FFI, GIL handling
- Memory safety in IPC between parent and worker processes
Architecture
crates/coglet/is the core: HTTP server, worker orchestration, IPCcrates/coglet-python/is PyO3 bindings for Python predictor integration- Two-process architecture: parent (HTTP + orchestrator) and worker (Python execution)
- Don't mix IPC concerns with HTTP handling
- Snapshot tests use
insta-- check if snapshots need updating
Dependencies
- New dependencies should be justified --
crates/deny.tomlaudits them - Prefer std or existing deps over adding new ones for small tasks
Related skills
AI & Agent Buildingagents