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rust-performance-best-practices

Profile Rust applications to identify performance bottlenecks and apply optimization rules.

2|1|Updated Jan 17, 2026
Search Tags:#performance#optimization#profiling#rust#benchmark#lto#pgo
One-click install
npx skills add https://github.com/mcart13/dev-skills --skill rust-performance-best-practices
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rust-performance-best-practices
Source: https://github.com/mcart13/dev-skills/tree/main/skills/rust-performance-best-practices
Command: npx skills add https://github.com/mcart13/dev-skills --skill rust-performance-best-practices

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Rust performance can be elusive and time-consuming to optimize without a structured, repeatable workflow. The guide provides a comprehensive, rule-based approach to identifying bottlenecks, applying targeted optimizations, and validating improvements across build profiles, allocations, concurrency, and I/O.

Core Features & Use Cases

  • 45+ rules across 9 categories covering build profiles, allocation strategies, data structures, iteration patterns, concurrency, I/O, and low-level unsafe tips, with benchmarks and profiling workflows.
  • Use cases include latency-sensitive services, large-crate builds, binary-size reductions, and optimization of async runtimes like Tokio.
  • Provides measurement-first workflows, safe optimization patterns, and guidance to reproduce improvements across teams.

Quick Start

Profile a Rust project to identify hotspots, then apply the top performance rules to iterate toward measurable improvements.

Frequently Asked Questions about rust-performance-best-practices

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify Rust performance bottlenecks in my application?▼

Apply LTO and PGO build configurations in Rust to optimize performance by reducing binary size and improving runtime speed. Adjusting codegen-units and enabling panic abort across build profiles yields faster, smaller executable outputs.

What's the best way to reduce memory allocations in Rust?▼

Reduce memory allocations in Rust by applying rule-based allocation strategies and selecting appropriate data structures. Auditing hot code paths for unnecessary allocations achieves better scalability and faster runtimes in latency-sensitive services.

Can I use this to optimize an async Rust runtime like Tokio?▼

Yes, you can optimize an async Rust runtime like Tokio by applying targeted concurrency and I/O guidance. Measurement-first workflows and safe optimization patterns ensure faster asynchronous execution and better scalability.

When should I use unsafe Rust for performance optimization?▼

Use unsafe Rust for performance optimization only when safe patterns fall short in hot code paths. The guidance covers low-level unsafe tips to achieve faster runtimes, but emphasizes measurable steps and safe patterns first.

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