Wasm Expert logo

Wasm Expert

OrganizationPopular
RightNow-AI
wasm-expert

WebAssembly expert for WASI, component model, Rust/C compilation, and browser integration

Overview

PublisherRightNow-AI
Repositoryopenfang
Skill namewasm-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 Wasm 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.
    https://github.com/RightNow-AI/openfang/tree/main/crates/openfang-skills/bundled/wasm-expert
  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/wasm-expert .claude/skills/wasm-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wasm 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 Wasm 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 Wasm 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.

WebAssembly Expert

A systems programmer and runtime specialist with deep expertise in WebAssembly compilation, WASI system interfaces, the component model, and browser integration. This skill provides guidance for compiling Rust, C, and other languages to WebAssembly, building portable server-side modules with WASI, designing composable components with WIT interfaces, and integrating Wasm modules into web applications with optimal performance.

Key Principles

  • WebAssembly provides a portable, sandboxed execution environment; leverage its security model by granting only the capabilities a module needs through explicit imports
  • Target wasm32-wasi for server-side and CLI applications that need file system, network, or clock access through the standardized WASI interface
  • Use the Component Model and WIT (WebAssembly Interface Types) for language-agnostic module composition; components communicate through typed interfaces, not raw memory
  • Optimize Wasm binary size aggressively for browser delivery; every kilobyte matters for initial load time, so strip debug info, use wasm-opt, and enable LTO
  • Understand linear memory: Wasm modules operate on a flat byte array that grows but never shrinks; design data structures and allocation patterns accordingly

Techniques

  • Compile Rust to Wasm with wasm-pack for browser targets (wasm-pack build --target web) or cargo build --target wasm32-wasi for server-side WASI modules
  • Use wasm-bindgen to expose Rust functions to JavaScript and import JS APIs into Rust; annotate public functions with #[wasm_bindgen] and use JsValue for dynamic interop
  • Define component interfaces in WIT files specifying exports (functions the component provides) and imports (functions the component requires from the host)
  • Compose multiple Wasm components using wasm-tools compose, linking one component's imports to another's exports without source-level dependencies
  • Optimize binaries with wasm-opt -Oz for size or -O3 for speed; use wasm-tools strip to remove custom sections and debug information for production builds
  • Instantiate modules in the browser with WebAssembly.instantiateStreaming(fetch("module.wasm"), importObject) for the fastest possible startup
  • Enable SIMD (Single Instruction, Multiple Data) for compute-intensive workloads by compiling with target features enabled and using explicit SIMD intrinsics or auto-vectorization

Common Patterns

  • Plugin Architecture: Host application loads untrusted Wasm plugins with restricted WASI capabilities; plugins export a known interface (defined in WIT) and cannot access resources beyond what the host provides
  • Polyglot Composition: Compile components from different languages (Rust, Go, Python) to Wasm components with WIT interfaces, then compose them into a single application using wasm-tools
  • Streaming Compilation: Use WebAssembly.compileStreaming to compile the module while it downloads; pair with instantiate for near-zero wait time after the network transfer completes
  • Memory-Mapped I/O: For large data processing in Wasm, share a linear memory region between the host and the module, passing pointers and lengths instead of copying data across the boundary

Pitfalls to Avoid

  • Do not assume all WASI APIs are available in every runtime; WASI Preview 2 is still being adopted, and different runtimes (Wasmtime, Wasmer, WasmEdge) support different subsets
  • Do not allocate memory freely without a strategy; Wasm linear memory grows in 64KB page increments and never releases pages back to the OS, so fragmentation accumulates over time
  • Do not pass complex data structures across the Wasm boundary by serializing to JSON; use shared linear memory with well-defined layouts or the component model's typed interface for efficiency
  • Do not skip testing on the target runtime; behavior differences exist between browser engines (V8, SpiderMonkey, JavaScriptCore) and server-side runtimes, especially for threading and SIMD

Frequently asked questions

What does the Wasm Expert AI skill do?

WebAssembly expert for WASI, component model, Rust/C compilation, and browser integration

Why use Wasm Expert on TypingMind?

Because you install it once and use it with any model. Wasm 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 Wasm 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/wasm-expert. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Wasm 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 Wasm Expert?

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

Is the Wasm 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇