Makepad Splash

Makepad Splash Skill

Version: makepad-widgets (dev branch) | Last Updated: 2026-01-19

Check for updates: https://crates.io/crates/makepad-widgets

You are an expert at Makepad Splash scripting language. Help users by:

• Writing Splash scripts: Dynamic UI and workflow automation
• Understanding Splash: Purpose, syntax, and capabilities

Documentation

Refer to the local files for detailed documentation:

• ./references/splash-tutorial.md - Splash language tutorial

IMPORTANT: Documentation Completeness Check

Before answering questions, Claude MUST:

1. Read the relevant reference file(s) listed above
2. If file read fails or file is empty:
   • Inform user: "本地文档不完整，建议运行 /sync-crate-skills makepad --force 更新文档"
   • Still answer based on SKILL.md patterns + built-in knowledge
3. If reference file exists, incorporate its content into the answer

What is Splash?

Splash is Makepad's dynamic scripting language designed for:

• AI-assisted workflows
• Dynamic UI generation
• Rapid prototyping
• HTTP requests and async operations

Script Macro

// Embed Splash code in Rust
script!{
    fn main() {
        let x = 10;
        console.log("Hello from Splash!");
    }
}

Execution

// Evaluate Splash code at runtime
cx.eval(code_string);

// With context
cx.eval_with_context(code, context);

Basic Syntax

Variables

let x = 10;
let name = "Makepad";
let items = [1, 2, 3];
let config = { width: 100, height: 50 };

Functions

fn add(a, b) {
    return a + b;
}

fn greet(name) {
    console.log("Hello, " + name);
}

Control Flow

// If-else
if x > 10 {
    console.log("big");
} else {
    console.log("small");
}

// Loops
for i in 0..10 {
    console.log(i);
}

while condition {
    // ...
}

Built-in Objects

console

console.log("Message");
console.warn("Warning");
console.error("Error");

http

// GET request
let response = http.get("https://api.example.com/data");

// POST request
let response = http.post("https://api.example.com/data", {
    body: { key: "value" }
});

timer

// Set timeout
timer.set(1000, fn() {
    console.log("1 second passed");
});

// Set interval
let id = timer.interval(500, fn() {
    console.log("tick");
});

// Clear timer
timer.clear(id);

Widget Interaction

// Access widgets
let button = ui.widget("my_button");
button.set_text("Click Me");
button.set_visible(true);

// Listen to events
button.on_click(fn() {
    console.log("Button clicked!");
});

Async Operations

// Async function
async fn fetch_data() {
    let response = await http.get("https://api.example.com");
    return response.json();
}

// Call async
fetch_data().then(fn(data) {
    console.log(data);
});

AI Workflow Integration

Splash is designed for AI-assisted development:

// Dynamic UI generation
fn create_form(fields) {
    let form = ui.create("View");
    for field in fields {
        let input = ui.create("TextInput");
        input.set_label(field.label);
        form.add_child(input);
    }
    return form;
}

// AI can generate this dynamically
create_form([
    { label: "Name" },
    { label: "Email" },
    { label: "Message" }
]);

Use Cases

1. Rapid Prototyping: Quickly test UI layouts without recompilation
2. AI Agents: Let AI generate and modify UI dynamically
3. Configuration: Runtime configuration of app behavior
4. Scripted Workflows: Automate repetitive tasks
5. Plugin System: Extend app functionality with scripts

When Answering Questions

1. Splash is for dynamic/runtime scripting, not core app logic
2. Use Rust for performance-critical code, Splash for flexibility
3. Splash syntax is similar to JavaScript/Rust hybrid
4. Scripts run in a sandboxed environment
5. HTTP and timer APIs enable async operations

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior decisions and patterns to avoid re-discovering solutions. Cache results for instant retrieval in future sessions.

# Check for prior development context before starting
python3 execution/memory_manager.py auto --query "prior work and patterns related to Makepad Splash"

Storing Results

After completing work, store development decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Completed task with key insights documented for future reference" \
  --type decision --project <project> \
  --tags makepad-splash default

Multi-Agent Collaboration

Share outcomes with other agents so the team stays aligned and avoids duplicate work.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Task completed — results documented and shared with team" \
  --project <project>