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Agents48k · #4671

molykit

Helps your agent manage AI conversations. It allows for smooth user interactions and the use of AI tools.

What it does

MolyKit is a toolkit for building AI chat applications that work across different operating systems. It helps connect with AI services like OpenAI and display conversations in an organized way.

When to use it

  • ✓When building an AI chat application.
  • ✓When integrating an AI service (like OpenAI) into your app.
  • ✓When you need your chat app to work on computers and the web.

Example of what to ask your AI

“How can I use MolyKit to create a chat interface with OpenAI?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/sickn33/agentic-awesome-skills/blob/main/skills/molykit/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/sickn33/agentic-awesome-skills/blob/main/skills/molykit/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

MolyKit provides ready-made components for displaying messages and text input fields, along with tools to efficiently and asynchronously connect with artificial intelligences, ensuring everything works well on different platforms.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add sickn33/agentic-awesome-skills --skill molykit

Or download just the file:

curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/skills/molykit/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

MolyKit Skill

Best practices for building AI chat interfaces with Makepad using MolyKit - a toolkit for cross-platform AI chat applications.

Source codebase: /Users/zhangalex/Work/Projects/FW/robius/moly/moly-kit

When to Use

Use this skill when:

  • Building AI chat interfaces with Makepad
  • Integrating OpenAI or other LLM APIs
  • Implementing cross-platform async for native and WASM
  • Creating chat widgets (messages, prompts, avatars)
  • Handling SSE streaming responses
  • Keywords: molykit, moly-kit, ai chat, bot client, openai makepad, chat widget, sse streaming

Overview

MolyKit provides:

  • Cross-platform async utilities (PlatformSend, spawn(), ThreadToken)
  • Ready-to-use chat widgets (Chat, Messages, PromptInput, Avatar)
  • BotClient trait for AI provider integration
  • OpenAI-compatible client with SSE streaming
  • Protocol types for messages, bots, and tool calls
  • MCP (Model Context Protocol) support

Cross-Platform Async Patterns

PlatformSend - Send Only on Native

/// Implies Send only on native platforms, not on WASM
/// - On native: implemented by types that implement Send
/// - On WASM: implemented by ALL types
pub trait PlatformSend: PlatformSendInner {}

/// Boxed future type for cross-platform use
pub type BoxPlatformSendFuture<'a, T> = Pin<Box<dyn PlatformSendFuture<Output = T> + 'a>>;

/// Boxed stream type for cross-platform use
pub type BoxPlatformSendStream<'a, T> = Pin<Box<dyn PlatformSendStream<Item = T> + 'a>>;

Platform-Agnostic Spawning

/// Runs a future independently
/// - Uses tokio on native (requires Send)
/// - Uses wasm-bindgen-futures on WASM (no Send required)
pub fn spawn(fut: impl PlatformSendFuture<Output = ()> + 'static);

// Usage
spawn(async move {
    let result = fetch_data().await;
    Cx::post_action(DataReady(result));
    SignalToUI::set_ui_signal();
});

Task Cancellation with AbortOnDropHandle

/// Handle that aborts its future when dropped
pub struct AbortOnDropHandle(AbortHandle);

// Usage - task cancelled when widget dropped
#[rust]
task_handle: Option<AbortOnDropHandle>,

fn start_task(&mut self) {
    let (future, handle) = abort_on_drop(async move {
        // async work...
    });
    self.task_handle = Some(handle);
    spawn(async move { let _ = future.await; });
}

ThreadToken for Non-Send Types on WASM

/// Store non-Send value in thread-local, access via token
pub struct ThreadToken<T: 'static>;

impl<T> ThreadToken<T> {
    pub fn new(value: T) -> Self;
    pub fn peek<R>(&self, f: impl FnOnce(&T) -> R) -> R;
    pub fn peek_mut<R>(&self, f: impl FnOnce(&mut T) -> R) -> R;
}

// Usage - wrap non-Send type for use across Send boundaries
let token = ThreadToken::new(non_send_value);
spawn(async move {
    token.peek(|value| {
        // use value...
    });
});

BotClient Trait

Implementing AI Provider Integration

pub trait BotClient: Send {
    /// Send message with streamed response
    fn send(
        &mut self,
        bot_id: &BotId,
        messages: &[Message],
        tools: &[Tool],
    ) -> BoxPlatformSendStream<'static, ClientResult<MessageContent>>;

    /// Get available bots/models
    fn bots(&self) -> BoxPlatformSendFuture<'static, ClientResult<Vec<Bot>>>;

    /// Clone for passing around
    fn clone_box(&self) -> Box<dyn BotClient>;
}

// Usage
let client = OpenAIClient::new("https://api.openai.com/v1".into());
client.set_key("sk-...")?;
let context = BotContext::from(client);

BotContext - Sharable Wrapper

/// Sharable wrapper with loaded bots for sync UI access
pub struct BotContext(Arc<Mutex<InnerBotContext>>);

impl BotContext {
    pub fn load(&mut self) -> BoxPlatformSendFuture<ClientResult<()>>;
    pub fn bots(&self) -> Vec<Bot>;
    pub fn get_bot(&self, id: &BotId) -> Option<Bot>;
    pub fn client(&self) -> Box<dyn BotClient>;
}

// Usage
let mut context = BotContext::from(client);
spawn(async move {
    if let Err(errors) = context.load().await.into_result() {
        // handle errors
    }
    Cx::post_action(BotsLoaded);
});

Protocol Types

Message Structure

pub struct Message {
    pub from: EntityId,         // User, System, Bot(BotId), App
    pub metadata: MessageMetadata,
    pub content: MessageContent,
}

pub struct MessageContent {
    pub text: String,           // Main content (markdown)
    pub reasoning: String,      // AI reasoning/thinking

…
FAQ

What is 'cross-platform async'?

It means the code can run asynchronously (without freezing the interface) on both native systems (like Windows, macOS) and the web (WASM), using the right tools for each environment.

What are 'chat widgets'?

These are pre-built user interface elements, such as the message display area, the text input box, and the avatar image, that MolyKit offers to simplify chat creation.

How does MolyKit connect to AI?

It uses a 'BotClient' that can be configured to communicate with different AI providers, like OpenAI, and receives responses in real-time (streaming).

Details

Original description by the author

CRITICAL: Use for MolyKit AI chat toolkit. Triggers on: BotClient, OpenAI, SSE streaming, AI chat, molykit, PlatformSend, spawn(), ThreadToken, cross-platform async, Chat widget, Messages, PromptInput, Avatar, LLM

repo: sickn33/agentic-awesome-skills

Popularity

GitHub stars
48k
Ranking position
#4671
License
MIT
Updated
10/15/2026

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