Rust Performance

Name: Rust Performance
Author: huiali

Checked

huiali·vlatest·backend·MIT

Helps with Rust, performance optimization as part of developing backend services and APIs workflows.

Repository

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terminal

$ npx skills add huiali/rust-skills --skill rust-performance -a claude-code

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What we know about this skill

Publisher

huiali

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Install target

Live repository

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Automated safety checks

scanned 1 Oct 2026

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
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No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned huiali/rust-skills at 947bf77509.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit: 947bf77509
Manifest: skills/rust-performance/SKILL.md
Scanned: 8 files, 1,470 lines
Copies in repo: 2 — all of them scanned

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About this skill

What it does

This skill optimizes Rust code for performance. It analyzes existing Rust code and suggests improvements, focusing on areas like memory management, data structure selection, and algorithmic efficiency. The goal is to reduce execution time and resource consumption in Rust applications.

When to use it

Profiling slow functions: Identify bottlenecks within a Rust program and receive targeted optimization suggestions.
Improving application responsiveness: Reduce latency in critical sections of code for a more responsive user experience.
Resource-constrained environments: Optimize memory usage and CPU utilization when deploying applications on devices with limited resources.
Benchmarking performance: Compare different implementation approaches to determine the most efficient solution.

Key capabilities

Code analysis for performance bottlenecks
Memory management optimization suggestions
Data structure selection recommendations
Algorithmic efficiency improvements

Example prompts

"Analyze this Rust function and suggest ways to improve its speed: [paste code]"
"What's the most efficient data structure for storing a large number of sorted integers in Rust?"
"How can I reduce memory allocations in this Rust program?"

Tips & gotchas

This skill requires access to the Rust source code being analyzed. The suggestions provided are recommendations; thorough testing is crucial after applying any optimization changes.