What is the Neural Link?

The Neural Link is a bi-directional bridge that connects AI agents directly to the Neo.mjs runtime. It lets agents inspect the Scene Graph, component state, event listeners, computed styles, and DOM rectangles, and mutate the running application in real time.

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

Neo.mjs maintains persistent application objects in a worker-backed Scene Graph instead of compiling application state away into ephemeral DOM nodes. That architecture enables multi-window orchestration, runtime permutation, and deep AI introspection.

What is Context Engineering?

Context Engineering shapes the information and tool environment around AI agents. Neo.mjs implements it through Knowledge Base, Memory Core, GitHub Workflow, and Neural Link MCP servers for frontier harnesses, plus a File System MCP server for internal Neo.ai.Agent local loops.

What is the Neo.mjs Agent OS?

The Neo.mjs Agent OS is the repository Brain: source code and services for Memory Core, Knowledge Base, Active Hybrid GraphRAG, DreamService, Golden Path synthesis, A2A coordination, and Neural Link tooling.

Frontmatter

id	9439
title	TreeStore: Apply "Anchor & Echo" JSDoc strategy for AI discoverability
state	Closed
labels	documentationenhancementai
assignees	tobiu
createdAt	Mar 11, 2026, 11:52 AM
updatedAt	Mar 11, 2026, 11:54 AM
githubUrl	https://github.com/neomjs/neo/issues/9439
author	tobiu
commentsCount	1
parentIssue	9404
subIssues	[]
subIssuesCompleted	0
subIssuesTotal	0
contentTrust
projected
quarantined	0
signals	[]
blockedBy	[]
blocking	[]
closedAt	Mar 11, 2026, 11:54 AM

TreeStore: Apply "Anchor & Echo" JSDoc strategy for AI discoverability

Closed v12.1.0/archive-v12-1-0-chunk-1 documentationenhancementai

tobiu commented on Mar 11, 2026, 11:52 AM

Background

The AI Knowledge Base parses and chunks source files (like TreeStore.mjs) by methods and properties. While the class-level documentation provided excellent context about the "Projection Architecture" and "Structural Layer", isolated method chunks (like expand() or collapse()) often lacked this semantic weight. This "Implied Context" anti-pattern leads to poor discoverability during vector searches.

Solution: Anchor & Echo Strategy

To balance human readability with AI discoverability, we are applying the "Anchor & Echo" strategy to TreeStore.mjs:

The Anchor: The class-level docblock and major overrides (splice, filter) establish high-value architectural vocabulary (e.g., "Structural Layer", "Projection Layer").
The Echo: Smaller fields and helper methods deliberately reuse this specific vocabulary instead of generic terms.

Changes Implemented

Private Maps (#allRecordsMap, #childrenMap): Now explicitly defined as the foundation and hierarchy of the Structural Layer.
collapse() & expand(): Clarified that they mathematically move nodes between the Structural Layer and the Projection Layer.
Collection Helpers (collectAllDescendants, collectVisibleDescendants): Updated to state they traverse the Structural Layer to build the Projection Layer or perform deep cleanup.
updateSiblingStats(): Anchored its purpose to operations within the Structural Layer.

These targeted JSDoc enhancements ensure that every chunk of TreeStore.mjs carries sufficient semantic weight for accurate and context-aware retrieval from the ChromaDB knowledge base.

tobiu Mar 11, 2026, 11:54 AM

Implemented the Anchor & Echo JSDoc strategy for TreeStore. Changes committed and pushed in d0dbcc500.