Tommy 用於迫使 AI 按嚴格架構生成程式碼的語言 tommylang

We all use ChatGPT, Claude, or Copilot to write code. It's great for simple scripts. But the moment you ask for a real Enterprise microservice (with Kafka, Redis, and Saga patterns), the AI gives you a massive wall of text.

You spend hours reviewing it, fixing missing dependencies, wiring up DI, and realizing it wrote an insecure SQL query.

I got so frustrated with this that I started asking a different question: What if I don't ask the AI to write code, but ask it to compile a strict architectural blueprint?

That's how tommylang was born.

🏛 What is tommylang?

It's an AI-native DSL with a custom file extension (.ty). You don't write public class UserService or async Task. You write pure intent.

Here is an example of a payment endpoint in Tommy:

[Saga]
[Outbox]
[Idempotent(key = 'order_id')]
[REST('/api/payments')]
[Auth(oauth2 = 'client_credentials')]
create_payment (@order_dto order) {
    ? order.amount <== 0.0 {
        <= bad_request('Amount must be greater than zero')
    }

    @db.query('INSERT INTO payments ...', { id = order.id })
    [Event('payment_created')].publish({ id = order.id })

    <= created('Payment processed')
}

When you run our CLI (tommycli), it sends this to GPT-4o with a strict System Prompt. The AI doesn't just write code; it generates a <pre-flight> architecture plan, UML diagrams, and idiomatic C#, Rust, or Python.

🚀 The Coolest Features

Here is what makes tommylang different from "just a prompt":

1. Semantic Typography (TommyColor)
We designed a custom VS Code theme where color represents architecture, not just syntax. Purple is for logic (if, return), Green is for Classes/Interfaces, Blue is for Functions, and White is for Variables. Code reviews become 10x faster.

2. Built-in Enterprise Patterns
You don't need to explain to the AI what a Saga or Circuit Breaker is. You just use [Saga] or [CircuitBreaker]. The prompt forces the AI to generate the exact framework implementations (e.g., MassTransit for C#, or Polly).

3. Polyglot by Design
Write once, compile anywhere. Tommy targets C#, Python, Rust, Go, PHP, and TypeScript. Because the blueprint is abstract, the AI doesn't carry over C#-specific boilerplate into Rust.

4. OS-Level & AI-Agents
It's not just for web dev. We have annotations for [Ring(0)] (bare-metal Rust #![no_std]) and [Agent] (LangChain / CrewAI integration).

🧠 How it works under the hood

Tommy uses the "prompt-as-compiler" approach. The entire logic lives in a single System Prompt (COMPILER_PROMPT.md).
It enforces strict rules: snake_case for functions, = for all data, and : only for logic. If the AI hallucinates, the prompt forces it to fail the AST dry-run.

🛠 Try it out

The project is in early Alpha, but you can test the VS Code theme and the CLI right now.

• VS Code Theme: TommyColor
• GitHub Repo: tommylang

I'd love to hear your thoughts. Is this something you would use for your next microservice, or is it overengineering? Let me know in the comments!