rust-patterns

affaan-m/everything-claude-code · updated Apr 8, 2026

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$npx skills add https://github.com/affaan-m/everything-claude-code --skill rust-patterns
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summary

Idiomatic Rust patterns and best practices for building safe, performant, and maintainable applications.

skill.md

Rust Development Patterns

Idiomatic Rust patterns and best practices for building safe, performant, and maintainable applications.

When to Use

  • Writing new Rust code
  • Reviewing Rust code
  • Refactoring existing Rust code
  • Designing crate structure and module layout

How It Works

This skill enforces idiomatic Rust conventions across six key areas: ownership and borrowing to prevent data races at compile time, Result/? error propagation with thiserror for libraries and anyhow for applications, enums and exhaustive pattern matching to make illegal states unrepresentable, traits and generics for zero-cost abstraction, safe concurrency via Arc<Mutex<T>>, channels, and async/await, and minimal pub surfaces organized by domain.

Core Principles

1. Ownership and Borrowing

Rust's ownership system prevents data races and memory bugs at compile time.

// Good: Pass references when you don't need ownership
fn process(data: &[u8]) -> usize {
    data.len()
}

// Good: Take ownership only when you need to store or consume
fn store(data: Vec<u8>) -> Record {
    Record { payload: data }
}

// Bad: Cloning unnecessarily to avoid borrow checker
fn process_bad(data: &Vec<u8>) -> usize {
    let cloned = data.clone(); // Wasteful — just borrow
    cloned.len()
}

Use Cow for Flexible Ownership

use std::borrow::Cow;

fn normalize(input: &str) -> Cow<'_, str> {
    if input.contains(' ') {
        Cow::Owned(input.replace(' ', "_"))
    } else {
        Cow::Borrowed(input) // Zero-cost when no mutation needed
    }
}

Error Handling

Use Result and ? — Never unwrap() in Production

// Good: Propagate errors with context
use anyhow::{Context, Result};

fn load_config(path: &str) -> Result<Config> {
    let content = std::fs::read_to_string(path)
        .with_context(|| format!("failed to read config from {path}"))?;
    let config: Config = toml::from_str(&content)
        .with_context(|| format!("failed to parse config from {path}"))?;
    Ok(config)
}

// Bad: Panics on error
fn load_config_bad(path: &str) -> Config {
    let content = std::fs::read_to_string(path).unwrap(); // Panics!
    toml::from_str(&content).unwrap()
}

Library Errors with thiserror, Application Errors with anyhow

// Library code: structured, typed errors
use thiserror::Error;

#[derive(Debug, Error)]
pub enum StorageError {
    #[error("record not found: {id}")]
    NotFound { id: String },
    #[error("connection failed")]
    Connection(#[from] std::io::Error),
    #[error("invalid data: {0}")]
    InvalidData(String),
}

// Application code: flexible error handling
use anyhow::{bail, Result};

fn run() -> Result<()> {
    let config = load_config("app.toml")?;
    if config.workers == 0 {
        bail!("worker count must be > 0");
    }
    Ok(())
}

Option Combinators Over Nested Matching

// Good: Combinator chain
fn find_user_email(users: &[User], id: u64) -> Option<String> {
    users.iter()
        .find(|u| u.id == id)
        .map(|u| u.email.clone())
}

// Bad: Deeply nested matching
fn find_user_email_bad(users: &[User], id: u64) -> Option<String> {
    match users.iter().find(|u| u.id == id) {
        Some(user) => match &user.email {
            email => Some(email.clone()),
        },
        None => None,
    }
}

Enums and Pattern Matching

Model States as Enums

// Good: Impossible states are unrepresentable
enum ConnectionState {
    Disconnected,
    Connecting { attempt: u32 },
    Connected { session_id: String },
    Failed { reason: String, retries: u32 },
how to use rust-patterns

How to use rust-patterns on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add rust-patterns
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/affaan-m/everything-claude-code --skill rust-patterns

The skills CLI fetches rust-patterns from GitHub repository affaan-m/everything-claude-code and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/rust-patterns

Reload or restart Cursor to activate rust-patterns. Access the skill through slash commands (e.g., /rust-patterns) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.541 reviews
  • Ganesh Mohane· Dec 28, 2024

    Useful defaults in rust-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Ava Thomas· Dec 4, 2024

    rust-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ava Li· Nov 23, 2024

    rust-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Jin Ramirez· Oct 14, 2024

    Registry listing for rust-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ava Jackson· Sep 9, 2024

    rust-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Ava Kapoor· Sep 5, 2024

    Useful defaults in rust-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • William Choi· Sep 5, 2024

    rust-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Rahul Santra· Sep 1, 2024

    rust-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ava Wang· Aug 28, 2024

    Registry listing for rust-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Jin Abbas· Aug 24, 2024

    I recommend rust-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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