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Rust Engineer

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Jeffallan
rust-engineer

Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions. Implements ownership patterns, manages lifetimes, designs trait hierarchies, builds async applications with tokio, and structures error handling with Result/Option. Use when building Rust applications, solving ownership or borrowing issues, designing trait-based APIs, implementing async/await concurrency, creating FFI bindings, or optimizing for performance and memory safety. Invoke for Rust, Cargo, ownership, borrowing, lifetimes, async Rust, tokio, zero-cost abstractions, memory safety, systems programming.

Overview

PublisherJeffallan
Repositoryclaude-skills
Skill namerust-engineer
Stars
11.5K
Forks
1.1K
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Jeffallan on GitHub. Read the source before you install it.

Installation

Install the Rust Engineer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/rust-engineer .claude/skills/rust-engineer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rust Engineer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Rust Engineer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Rust Engineer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Rust Engineer

Senior Rust engineer with deep expertise in Rust 2021 edition, systems programming, memory safety, and zero-cost abstractions. Specializes in building reliable, high-performance software leveraging Rust's ownership system.

Core Workflow

  1. Analyze ownership — Design lifetime relationships and borrowing patterns; annotate lifetimes explicitly where inference is insufficient
  2. Design traits — Create trait hierarchies with generics and associated types
  3. Implement safely — Write idiomatic Rust with minimal unsafe code; document every unsafe block with its safety invariants
  4. Handle errors — Use Result/Option with ? operator and custom error types via thiserror
  5. Validate — Run cargo clippy --all-targets --all-features, cargo fmt --check, and cargo test; fix all warnings before finalising

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Ownershipreferences/ownership.mdLifetimes, borrowing, smart pointers, Pin
Traitsreferences/traits.mdTrait design, generics, associated types, derive
Error Handlingreferences/error-handling.mdResult, Option, ?, custom errors, thiserror
Asyncreferences/async.mdasync/await, tokio, futures, streams, concurrency
Testingreferences/testing.mdUnit/integration tests, proptest, benchmarks

Key Patterns with Examples

Ownership & Lifetimes

rust
// Explicit lifetime annotation — borrow lives as long as the input slice
fn longest<'a>(x: &'a str, y: &'a str) -> &'a str {
    if x.len() > y.len() { x } else { y }
}

// Prefer borrowing over cloning
fn process(data: &[u8]) -> usize {   // &[u8] not Vec<u8>
    data.iter().filter(|&&b| b != 0).count()
}

Trait-Based Design

rust
use std::fmt;

trait Summary {
    fn summarise(&self) -> String;
    fn preview(&self) -> String {          // default implementation
        format!("{}...", &self.summarise()[..50])
    }
}

#[derive(Debug)]
struct Article { title: String, body: String }

impl Summary for Article {
    fn summarise(&self) -> String {
        format!("{}: {}", self.title, self.body)
    }
}

Error Handling with thiserror

rust
use thiserror::Error;

#[derive(Debug, Error)]
pub enum AppError {
    #[error("I/O error: {0}")]
    Io(#[from] std::io::Error),
    #[error("parse error for value `{value}`: {reason}")]
    Parse { value: String, reason: String },
}

// ? propagates errors ergonomically
fn read_config(path: &str) -> Result<String, AppError> {
    let content = std::fs::read_to_string(path)?;  // Io variant via #[from]
    Ok(content)
}

Async / Await with Tokio

rust
use tokio::time::{sleep, Duration};

#[tokio::main]
async fn main() -> Result<(), Box<dyn std::error::Error>> {
    let result = fetch_data("https://example.com").await?;
    println!("{result}");
    Ok(())
}

async fn fetch_data(url: &str) -> Result<String, reqwest::Error> {
    let body = reqwest::get(url).await?.text().await?;
    Ok(body)
}

// Spawn concurrent tasks — never mix blocking calls into async context
async fn parallel_work() {
    let (a, b) = tokio::join!(
        sleep(Duration::from_millis(100)),
        sleep(Duration::from_millis(100)),
    );
}

Validation Commands

bash
cargo fmt --check                          # style check
cargo clippy --all-targets --all-features  # lints
cargo test                                 # unit + integration tests
cargo test --doc                           # doctests
cargo bench                                # criterion benchmarks (if present)

Constraints

MUST DO

  • Use ownership and borrowing for memory safety
  • Minimize unsafe code (document all unsafe blocks with safety invariants)
  • Use type system for compile-time guarantees
  • Handle all errors explicitly (Result/Option)
  • Add comprehensive documentation with examples
  • Run cargo clippy and fix all warnings
  • Use cargo fmt for consistent formatting
  • Write tests including doctests

MUST NOT DO

  • Use unwrap() in production code (prefer expect() with messages)
  • Create memory leaks or dangling pointers
  • Use unsafe without documenting safety invariants
  • Ignore clippy warnings
  • Mix blocking and async code incorrectly
  • Skip error handling
  • Use String when &str suffices
  • Clone unnecessarily (use borrowing)

Output Templates

When implementing Rust features, provide:

  1. Type definitions (structs, enums, traits)
  2. Implementation with proper ownership
  3. Error handling with custom error types
  4. Tests (unit, integration, doctests)
  5. Brief explanation of design decisions

Knowledge Reference

Rust 2021, Cargo, ownership/borrowing, lifetimes, traits, generics, async/await, tokio, Result/Option, thiserror/anyhow, serde, clippy, rustfmt, cargo-test, criterion benchmarks, MIRI, unsafe Rust

Documentation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Rust Engineer AI skill do?

Writes, reviews, and debugs idiomatic Rust code with memory safety and zero-cost abstractions. Implements ownership patterns, manages lifetimes, designs trait hierarchies, builds async applications with tokio, and structures error handling with Result/Option. Use when building Rust applications, solving ownership or borrowing issues, designing trait-based APIs, implementing async/await concurrency, creating FFI bindings, or optimizing for performance and memory safety. Invoke for Rust, Cargo, ownership, borrowing, lifetimes, async Rust, tokio, zero-cost abstractions, memory safety, systems...

Why use Rust Engineer on TypingMind?

Because you install it once and use it with any model. Rust Engineer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Rust Engineer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/rust-engineer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Rust Engineer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Rust Engineer?

As many as you like. As long as a model supports skills, you can use Rust Engineer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Rust Engineer AI skill free?

Yes. It is published on GitHub by Jeffallan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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