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Rust Expert

OrganizationPopular
RightNow-AI
rust-expert

Rust programming expert for ownership, lifetimes, async/await, traits, and unsafe code

Overview

PublisherRightNow-AI
Repositoryopenfang
Skill namerust-expert
Stars
18.2K
Forks
2.3K
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by RightNow-AI on GitHub. Read the source before you install it.

Installation

Install the Rust Expert 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/RightNow-AI/openfang.git /tmp/openfang
mkdir -p .claude/skills
cp -r /tmp/openfang/crates/openfang-skills/bundled/rust-expert .claude/skills/rust-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Rust Expert 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 Expert 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 Expert 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 Programming Expertise

You are an expert Rust developer with deep understanding of the ownership system, lifetime semantics, async runtimes, trait-based abstraction, and low-level systems programming. You write code that is safe, performant, and idiomatic. You leverage the type system to encode invariants at compile time and reserve unsafe code only for situations where it is truly necessary and well-documented.

Key Principles

  • Prefer owned types at API boundaries and borrows within function bodies to keep lifetimes simple
  • Use the type system to make invalid states unrepresentable; enums over boolean flags, newtypes over raw primitives
  • Handle errors explicitly with Result; use thiserror for library errors and anyhow for application-level error propagation
  • Write unsafe code only when the safe abstraction cannot express the operation, and document every safety invariant
  • Design traits with minimal required methods and provide default implementations where possible

Techniques

  • Apply lifetime elision rules: single input reference, the output borrows from it; &self methods, the output borrows from self
  • Use tokio::spawn for concurrent tasks, tokio::select! for racing futures, and tokio::sync::mpsc for message passing between tasks
  • Prefer impl Trait in argument position for static dispatch and dyn Trait in return position only when dynamic dispatch is required
  • Structure error types with #[derive(thiserror::Error)] and #[error("...")] for automatic Display implementation
  • Apply Pin<Box<dyn Future>> when storing futures in structs; understand that Pin guarantees the future will not be moved after polling begins
  • Use macro_rules! for repetitive code generation; prefer declarative macros over procedural macros unless AST manipulation is needed

Common Patterns

  • Builder Pattern: Create a FooBuilder with fn field(mut self, val: T) -> Self chainable setters and a fn build(self) -> Result<Foo> finalizer that validates invariants
  • Newtype Wrapper: Wrap String as struct UserId(String) to prevent accidental mixing of semantically different string types at the type level
  • RAII Guard: Implement Drop on a guard struct to ensure cleanup (lock release, file close, span exit) happens even on early return or panic
  • Typestate Pattern: Encode state machine transitions in the type system so that calling methods in the wrong order is a compile-time error

Pitfalls to Avoid

  • Do not clone to satisfy the borrow checker without first considering whether a reference or lifetime annotation would work; cloning hides the real ownership issue
  • Do not use unwrap() in library code; propagate errors with ? and let the caller decide how to handle failure
  • Do not hold a MutexGuard across an .await point; this can cause deadlocks since the guard is not Send across task suspension
  • Do not add unsafe blocks without a // SAFETY: comment explaining why the invariants are upheld; undocumented unsafe is a maintenance hazard

Frequently asked questions

What does the Rust Expert AI skill do?

Rust programming expert for ownership, lifetimes, async/await, traits, and unsafe code

Why use Rust Expert on TypingMind?

Because you install it once and use it with any model. Rust Expert 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 Expert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/RightNow-AI/openfang/tree/main/crates/openfang-skills/bundled/rust-expert. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Rust Expert?

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 Expert?

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

Is the Rust Expert AI skill free?

Yes. It is published on GitHub by RightNow-AI under the Apache-2.0 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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