> For the complete documentation index, see [llms.txt](https://docs.mira-ai-agent.vip/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.mira-ai-agent.vip/agent/editor.md).

# The Architecture

#### **Voice Layer**

The human-to-machine interface.\
This is where you *speak your intent*, and Mira translates it into structured logic.\
Powered by a multimodal recognition engine, it enables:

* Natural voice-to-code execution
* Voice-based wallet management
* On-chain commands spoken in real time

Example:

> “Mira, deploy a token on Solana named MIRA with 10B supply and lock liquidity for 30 days.”\
> → Mira executes the transaction and returns the CA in seconds.

#### **x402 Protocol**

The **neural network backbone** — inspired by the structure of agent cooperation.

**x402** acts as the bridge between **AI cognition** and **Web3 execution**, allowing Mira’s subsystems to:

* Share compute through decentralized nodes
* Sync state between off-chain AI reasoning and on-chain logic
* Create multi-agent contracts and micro-economies

It’s where AI agents don’t just think — they transact.

***

#### **Chat Agent Layer**

This is the **soul of Mira**.\
A conversational intelligence that learns your building style, remembers your stack preferences, and adapts with every deployment.

The chat agent can:

* Write, audit, and deploy smart contracts
* Manage tokenomics and DAO proposals
* Create and host front-end dApps
* Interact with any Web3 API

In the Mira ecosystem, **every chat is a build session**.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.mira-ai-agent.vip/agent/editor.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
