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	9133
title	Tune Spider Strategy Probabilities and Enhance Documentation
state	Closed
labels	documentationairefactoring
assignees	tobiu
createdAt	Feb 13, 2026, 2:45 AM
updatedAt	Feb 13, 2026, 2:48 AM
githubUrl	https://github.com/neomjs/neo/issues/9133
author	tobiu
commentsCount	1
parentIssue	9106
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
blockedBy	[]
blocking	[]
closedAt	Feb 13, 2026, 2:48 AM

Tune Spider Strategy Probabilities and Enhance Documentation

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

Closed v12.0.0 documentationairefactoring

tobiu commented on Feb 13, 2026, 2:45 AM

We are tuning the Spider's discovery probability distribution to prioritize the new "Network Walker" strategy. Since the repository search space is becoming saturated (15k users found), traversing the social graph of these qualified users is now the highest-yield strategy.

Changes:

Rebalance Probabilities:
- Network Walker: Increase from 15% to **30%**.
- High Stars: Decrease from 30% to **25%**.
- Bio Signals / Community: Decrease to ~5%.
- Stargazer: Decrease to ~5%.
Knowledge Base Enhancement: Add rich, intent-driven JSDoc to Spider.mjs explaining the "Filter Bubble" problem and why the Network Walker is the solution for the current stage of the index.

This shift marks a transition from "Breadth-First Repository Scanning" to "Depth-First Network Traversal".

tobiu added the documentation label on Feb 13, 2026, 2:45 AM

tobiu added the ai label on Feb 13, 2026, 2:45 AM

tobiu added the refactoring label on Feb 13, 2026, 2:45 AM

tobiu added parent issue #9106 on Feb 13, 2026, 2:45 AM

tobiu assigned to @tobiu on Feb 13, 2026, 2:45 AM

tobiu referenced in commit b4fee22 - "feat(devindex): Tune spider strategies & prioritize network walker (#9133)" on Feb 13, 2026, 2:48 AM

tobiu Feb 13, 2026, 2:48 AM

Input from Gemini 3 Pro:

✦ I have tuned the Spider's strategy probabilities and enhanced the documentation.

Changes:

Rebalanced Probabilities:

Network Walker: 30% (Primary)

High Stars: 25%

Keyword: 20%

Temporal: 15%

Community/Bio: 5%

Stargazer: 5%

CLI Update: Added "🕸️ Network Walker" to the interactive menu in Manager.mjs.

Documentation: Added intent-driven JSDoc to Spider.mjs explaining the "Filter Bubble" problem and the strategic shift to Depth-First traversal.

This configuration positions the "Network Walker" as the primary engine for discovering high-quality candidates beyond the saturated top-repo layer.

tobiu closed this issue on Feb 13, 2026, 2:48 AM