agentleFS
taixuanntaixuann/development-space/.claude/skills/calling-rust-from-tauri-frontend/SKILL.md

calling-rust-from-tauri-frontend

Skill1 starsChanged 14 days agoMITView on GitHub

Guides the user through calling Rust backend functions from the Tauri frontend using the invoke function, defining commands with the #[tauri::command] attribute, passing arguments, returning values, handling errors, and implementing async IPC communication.

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 1 is distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Use the #[tauri::command] attribute macro:

    line 20
  2. Very specific:

    Use rename_all to change the naming convention:

    line 77
  3. Very specific:

    Use the async keyword:

    line 273
  4. Distinctive:

    Create a typed wrapper:

    line 443

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Calling Rust from Tauri Frontend

This skill covers how to call Rust backend functions from your Tauri v2 frontend using the command system and invoke function.

Overview

Tauri provides two IPC mechanisms:

  • Commands (recommended): Type-safe function calls with serialized arguments/return values
  • Events: Dynamic, one-way communication (not covered here)

Basic Commands

Defining a Command in Rust

Use the #[tauri::command] attribute macro:

// src-tauri/src/lib.rs
#[tauri::command]
fn greet(name: String) -> String {
    format!("Hello, {}!", name)
}

Registering Commands

Commands must be registered with the invoke handler:

#[cfg_attr(mobile, tauri::mobile_entry_point)]
pub fn run() {
    tauri::Builder::default()
        .invoke_handler(tauri::generate_handler![greet, login, fetch_data])
        .run(tauri::generate_context!())
        .expect("error while running tauri application")
}

Invoking from JavaScript/TypeScript

import { invoke } from '@tauri-apps/api/core';

const greeting = await invoke('greet', { name: 'World' });
console.log(greeting); // "Hello, World!"

Or with the global Tauri object (when app.withGlobalTauri is enabled):

const { invoke } = window.__TAURI__.core;
const greeting = await invoke('greet', { name: 'World' });

Passing Arguments

Argument Naming Convention

By default, Rust snake_case arguments map to JavaScript camelCase:

#[tauri::command]
fn create_user(user_name: String, user_age: u32) -> String {
    format!("{} is {} years old", user_name, user_age)
}
await invoke('create_user', { userName: 'Alice', userAge: 30 });

Use rename_all to change the naming convention:

#[tauri::command(rename_all = "snake_case")]
fn create_user(user_name: String, user_age: u32) -> String {
    format!("{} is {} years old", user_name, user_age)
}

Complex Arguments

Arguments must implement serde::Deserialize:

use serde::Deserialize;

#[derive(Deserialize)]
struct UserData {
    name: String,
    email: String,
    age: u32,
}

#[tauri::command]
fn register_user(user: UserData) -> String {
    format!("Registered {} ({}) age {}", user.name, user.email, user.age)
}
await invoke('register_user', {
    user: { name: 'Alice', email: 'alice@example.com', age: 30 }
});

Returning Values

Simple Return Types

Return types must implement serde::Serialize:

#[tauri::command]
fn get_count() -> i32 { 42 }

#[tauri::command]
fn get_message() -> String { "Hello from Rust!".into() }
const count: number = await invoke('get_count');
const message: string = await invoke('get_message');

Returning Complex Types

use serde::Serialize;

#[derive(Serialize)]
struct AppConfig {
    theme: String,
    language: String,
    notifications_enabled: bool,
}

#[tauri::command]
fn get_config() -> AppConfig {
    AppConfig {
        theme: "dark".into(),
        language: "en".into(),
        notifications_enabled: true,
    }
}
interface AppConfig {
    theme: string;
    language: string;
    notificationsEnabled: boolean;
}
const config: AppConfig = await invoke('get_config');

Returning Binary Data

For large binary data, use tauri::ipc::Response to bypass JSON serialization:

use tauri::ipc::Response;

#[tauri::command]
fn read_file(path: String) -> Response {
    let data = std::fs::read(&path).unwrap();
    Response::new(data)
}
const data: ArrayBuffer = await invoke('read_file', { path: '/path/to/file' });

Error Handling

Using Result Types

Return Result<T, E> where E implements Serialize or is a String:

#[tauri::command]
fn divide(a: f64, b: f64) -> Result<f64, String> {
    if b == 0.0 {
        Err("Cannot divide by zero".into())
    } else {
        Ok(a / b)
    }
}
try {
    const result = await invoke('divide', { a: 10, b: 0 });
} catch (error) {
    console.error('Error:', error); // "Cannot divide by zero"
}

Custom Error Types with thiserror

use serde::Serialize;
use thiserror::Error;

#[derive(Debug, Error)]
enum AppError {
    #[error("File not found: {0}")]
    FileNotFound(String),
    #[error("Permission denied")]
    PermissionDenied,
    #[error("IO error: {0}")]
    Io(#[from] std::io::Error),
}

impl Serialize for AppError {
    fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>
    where S: serde::ser::Serializer {
        serializer.serialize_str(self.to_string().as_ref())
    }
}

#[tauri::command]
fn open_file(path: String) -> Result<String, AppError> {
    if !std::path::Path::new(&path).exists() {
        return Err(AppError::FileNotFound(path));
    }
    let content = std::fs::read_to_string(&path)?;
    Ok(content)
}

Structured Error Responses

use serde::Serialize;

#[derive(Debug, Serialize)]
struct ErrorResponse { code: String, message: String }

#[tauri::command]
fn validate_input(input: String) -> Result<String, ErrorResponse> {
    if input.is_empty() {
        return Err(ErrorResponse {
            code: "EMPTY_INPUT".into(),
            message: "Input cannot be empty".into(),
        });
    }
    Ok(input.to_uppercase())
}
interface ErrorResponse { code: string; message: string; }

try {
    const result = await invoke('validate_input', { input: '' });
} catch (error) {
    const err = error as ErrorResponse;
    console.error(`Error ${err.code}: ${err.message}`);
}

Async Commands

Defining Async Commands

Use the async keyword:

#[tauri::command]
async fn fetch_data(url: String) -> Result<String, String> {
    let response = reqwest::get(&url).await.map_err(|e| e.to_string())?;
    let body = response.text().await.map_err(|e| e.to_string())?;
    Ok(body)
}

Async with Borrowed Types Limitation

Async commands cannot use borrowed types like &str directly:

// Will NOT compile:
// async fn bad_command(value: &str) -> String { ... }

// Use owned types instead:
#[tauri::command]
async fn good_command(value: String) -> String {
    some_async_operation(&value).await;
    value
}

// Or wrap in Result as workaround:
#[tauri::command]
async fn with_borrowed(value: &str) -> Result<String, ()> {
    some_async_operation(value).await;
    Ok(value.to_string())
}

Frontend Invocation

Async commands work identically to sync since invoke returns a Promise:

const result = await invoke('fetch_data', { url: 'https://api.example.com/data' });

Accessing Tauri Internals

WebviewWindow, AppHandle, and State

use std::sync::Mutex;

struct AppState { counter: Mutex<i32> }

#[tauri::command]
async fn get_window_label(window: tauri::WebviewWindow) -> String {
    window.label().to_string()
}

#[tauri::command]
async fn get_app_version(app: tauri::AppHandle) -> String {
    app.package_info().version.to_string()
}

#[tauri::command]
fn increment_counter(state: tauri::State<AppState>) -> i32 {
    let mut counter = state.counter.lock().unwrap();
    *counter += 1;
    *counter
}

pub fn run() {
    tauri::Builder::default()
        .manage(AppState { counter: Mutex::new(0) })
        .invoke_handler(tauri::generate_handler![
            get_window_label, get_app_version, increment_counter
        ])
        .run(tauri::generate_context!())
        .expect("error while running tauri application")
}

Advanced Features

Raw Request Access

Access headers and raw body:

use tauri::ipc::{Request, InvokeBody};

#[tauri::command]
fn upload(request: Request) -> Result<String, String> {
    let InvokeBody::Raw(data) = request.body() else {
        return Err("Expected raw body".into());
    };
    let auth = request.headers()
        .get("Authorization")
        .and_then(|v| v.to_str().ok())
        .ok_or("Missing Authorization header")?;
    Ok(format!("Received {} bytes", data.len()))
}
const data = new Uint8Array([1, 2, 3, 4, 5]);
await invoke('upload', data, { headers: { Authorization: 'Bearer token123' } });

Channels for Streaming

use tauri::ipc::Channel;
use tokio::io::AsyncReadExt;

#[tauri::command]
async fn stream_file(path: String, channel: Channel<Vec<u8>>) -> Result<(), String> {
    let mut file = tokio::fs::File::open(&path).await.map_err(|e| e.to_string())?;
    let mut buffer = vec![0u8; 4096];
    loop {
        let len = file.read(&mut buffer).await.map_err(|e| e.to_string())?;
        if len == 0 { break; }
        channel.send(buffer[..len].to_vec()).map_err(|e| e.to_string())?;
    }
    Ok(())
}
import { Channel } from '@tauri-apps/api/core';

const channel = new Channel<Uint8Array>();
channel.onmessage = (chunk) => console.log('Received:', chunk.length, 'bytes');
await invoke('stream_file', { path: '/path/to/file', channel });

Organizing Commands in Modules

// src-tauri/src/commands/user.rs
use serde::{Deserialize, Serialize};

#[derive(Deserialize)]
pub struct CreateUserRequest { pub name: String, pub email: String }

#[derive(Serialize)]
pub struct User { pub id: u32, pub name: String, pub email: String }

#[tauri::command]
pub fn create_user(request: CreateUserRequest) -> User {
    User { id: 1, name: request.name, email: request.email }
}
// src-tauri/src/commands/mod.rs
pub mod user;
// src-tauri/src/lib.rs
mod commands;

pub fn run() {
    tauri::Builder::default()
        .invoke_handler(tauri::generate_handler![commands::user::create_user])
        .run(tauri::generate_context!())
        .expect("error while running tauri application")
}

TypeScript Type Safety

Create a typed wrapper:

import { invoke } from '@tauri-apps/api/core';

export interface User { id: number; name: string; email: string; }
export interface CreateUserRequest { name: string; email: string; }

export const commands = {
    createUser: (request: CreateUserRequest): Promise<User> =>
        invoke('create_user', { request }),
    greet: (name: string): Promise<string> =>
        invoke('greet', { name }),
};

// Usage
const user = await commands.createUser({ name: 'Bob', email: 'bob@example.com' });

Quick Reference

TaskRustJavaScript
Define command#[tauri::command] fn name() {}-
Register commandtauri::generate_handler![name]-
Invoke command-await invoke('name', { args })
Return value-> T where T: Serializeconst result = await invoke(...)
Return error-> Result<T, E>try/catch
Async commandasync fn name()Same as sync
Access windowwindow: tauri::WebviewWindow-
Access appapp: tauri::AppHandle-
Access statestate: tauri::State<T>-

Key Constraints

  1. Command names must be unique across the entire application
  2. Commands in lib.rs cannot be pub (use modules for organization)
  3. All commands must be registered in a single generate_handler! call
  4. Async commands cannot use borrowed types like &str directly
  5. Arguments must implement Deserialize, return types must implement Serialize

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.