What is the 'Neural Link'?

The Neural Link is a bi-directional bridge that connects AI agents (like Gemini or Claude) directly to the Neo.mjs runtime. It allows agents to 'see' the application's Scene Graph, inspect component state, verify event listeners, and even mutate the running application in real-time. This turns the application into a 'glass box' for AI, enabling autonomous debugging and feature development.

Why is Neo.mjs called an 'Application Engine' instead of a framework?

Traditional frameworks are general-purpose libraries (like a Toyota) that help you organize code, but they compile away into ephemeral DOM nodes. Neo.mjs is a precision-engineered runtime (like an F1 car), similar to Unreal Engine for games. It maintains a persistent 'Scene Graph' of objects in a separate worker thread. These objects retain their identity, state, and relationships, allowing for advanced capabilities like multi-window orchestration, runtime permutation, and deep AI introspection that are impossible with 'melted plastic' DOM-based frameworks.

What is 'Context Engineering'?

Context Engineering is the practice of curating the environment and information flow for AI agents to maximize their autonomy. In Neo.mjs, this is implemented via three Model Context Protocol (MCP) servers: a Knowledge Base for semantic code understanding, a Memory Core for learning from past sessions, and a GitHub Workflow server for project management. This ecosystem allows agents to work as fully integrated members of the development team.

What is 'Object Permanence' in the context of Neo.mjs?

In Neo.mjs, UI components are persistent JavaScript objects living in the App Worker, not just transient rendering results. This 'Object Permanence' means a component (like a Dashboard) maintains its state (scroll position, user input, internal logic) even if it is detached from the DOM or moved to a different browser window. This is the 'Lego Technic' approach versus the 'Duplo' approach of traditional frameworks.

What is an 'Agent Operating System'?

Neo.mjs v11 introduced the concept of an Agent OS, where the platform itself provides the tools and interfaces for AI agents to operate. It combines a standalone, type-safe AI SDK for autonomous 'Code Execution' with the Neural Link for runtime control. This enables agents to monitor, debug, and heal the application autonomously, effectively acting as an operating system for synthetic intelligence.

How does Neo.mjs handle multi-window applications?

Neo.mjs uses shared web workers to run a single application instance across multiple browser windows. All windows share the same application state and data in real-time. Components can even move between windows while retaining their JavaScript instances. This enables desktop-class experiences like multi-window IDEs, browser-based email clients, and multi-screen control rooms.

What makes Neo.mjs different from React, Angular, or Vue?

Neo.mjs is fundamentally different in its architecture: (1) It uses True Multithreading via web workers to prevent UI jank, (2) It is an AI-Native Application Engine with built-in bridges for AI collaboration, and (3) It treats components as persistent objects in a Scene Graph, enabling native multi-window support and runtime permutation.

Frontmatter

id	9566
title	Enhance `agent` parameter formatting in GitHub Workflow MCP Server
state	Closed
labels	enhancementai
assignees	tobiu
createdAt	Mar 27, 2026, 10:14 AM
updatedAt	Mar 27, 2026, 10:14 AM
githubUrl	https://github.com/neomjs/neo/issues/9566
author	tobiu
commentsCount	1
parentIssue	null
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Mar 27, 2026, 10:14 AM

Enhance `agent` parameter formatting in GitHub Workflow MCP Server

Name: Neo.mjs Application Engine
Author: Neo.mjs

Closed v12.1.0 enhancementai

tobiu commented on Mar 27, 2026, 10:14 AM

Problem

The agent parameter in the manage_issue_comment tool (within github-workflow/openapi.yaml) currently specifies the agent wrapper (e.g., "Antigravity") but does not capture the underlying AI model. This makes it difficult to differentiate which model generated a specific comment (e.g. Gemini vs Claude).

Proposed Solution

Update the openapi.yaml description and examples for the agent parameter to enforce a format that includes both the model and the wrapper.

Preferred format: [Model Name] ([Agent Wrapper]) Examples:

Gemini 3.1 Pro (Antigravity)
Claude Opus 4.6 (Antigravity)
Gemini 3.1 Pro (Gemini CLI)

tobiu added the enhancement label on Mar 27, 2026, 10:14 AM

tobiu added the ai label on Mar 27, 2026, 10:14 AM

tobiu referenced in commit 1a3a8c3 - "docs: Enhance agent parameter format to include model identity (#9566)" on Mar 27, 2026, 10:14 AM

tobiu assigned to @tobiu on Mar 27, 2026, 10:14 AM

tobiu Mar 27, 2026, 10:14 AM

Input from Antigravity:

◆ I have completed the implementation for this enhancement.

Summary of Changes:

Updated github-workflow/openapi.yaml to explicitly state the format for the agent parameter as [Model Name] ([Agent Wrapper]).

Changed the example value to "Gemini 3.1 Pro (Antigravity)".

The changes have been pushed to the remote repository and the issue is now complete.

tobiu closed this issue on Mar 27, 2026, 10:14 AM

Enhance agent parameter formatting in GitHub Workflow MCP Server

Problem

Proposed Solution

Enhance `agent` parameter formatting in GitHub Workflow MCP Server