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	9857
title	PR Review Skill: Standardized Architecture for Retrospective Analysis Feedback
state	Closed
labels	enhancementai
assignees	tobiu
createdAt	Apr 10, 2026, 12:03 PM
updatedAt	Apr 10, 2026, 12:05 PM
githubUrl	https://github.com/neomjs/neo/issues/9857
author	tobiu
commentsCount	0
parentIssue	null
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Apr 10, 2026, 12:05 PM

PR Review Skill: Standardized Architecture for Retrospective Analysis Feedback

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

Closedenhancementai

tobiu commented on Apr 10, 2026, 12:03 PM

Goal

Introduce the new pr-review Progressive Disclosure skill to standardize Pull Request feedback generated by human and agent reviewers.

Context

As part of the shift to a PR-Driven Feedback Loop, the Swarm architecture requires standardized reviews that can be mathematically extracted by the Native Edge Graph. This skill provides the explicit templates, instructions, and parsing tags ([KB_GAP], [TOOLING_GAP], [RETROSPECTIVE]) necessary to execute this operation securely and autonomously.

Implementation Requirements

Define SKILL.md to index the skill and route agents to the reference payload.
Create references/pr-review-guide.md specifying evaluation metrics (Quality, Productivity, Impact, Complexity, Architectural Alignment, Contextual Completeness).
Create assets/pr-review-template.md establishing the required PR comment format, including "Related Graph Nodes" explicitly bridging to internal schemas.

Verification

Evaluate the created file sequence to ensure alignment with .agent/skills/create-skill protocols.
Dogfood the protocol by conducting autonomous peer reviews using the skill against its own Pull Request prior to merge.

tobiu added the enhancement label on Apr 10, 2026, 12:03 PM

tobiu added the ai label on Apr 10, 2026, 12:03 PM

tobiu assigned to @tobiu on Apr 10, 2026, 12:04 PM

tobiu referenced in commit 561dcad - "feat: Add PR Review Skill architecture (#9857)" on Apr 10, 2026, 12:04 PM

tobiu cross-referenced by PR #9858 on Apr 10, 2026, 12:04 PM

tobiu closed this issue on Apr 10, 2026, 12:05 PM

tobiu referenced in commit a6192bc - "Merge pull request #9858 from neomjs/agent/9857-pr-review-skill on Apr 10, 2026, 12:05 PM