feat(wiki): ingest nexus-spatial-discovery — 8-agent product discovery exercise

Ingest raw/Agent/agency-agents/examples/nexus-spatial-discovery.md
Source: 8 The Agency agents parallel discovery exercise for Nexus Spatial
Products: AI spatial command center (SpatialAIOps category)
Key findings: 2D-first/WebXR strategy, debugging as killer use case

Entities created: Nexus-Spatial, CrewAI
Concepts created: SpatialAIOps, Command-Theater-Interface,
  Debugging-Visualization, Semantic-Zoom, Growth-Loop
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---
title: "Command Theater Interface"
type: concept
tags: [spatial-computing, xr, interface-design, ux]
last_updated: 2026-03-05
---
## Definition
命令剧院Command Theater——以用户为中心的空间界面布局范式以弧形剧场形式围绕用户组织内容。源自 [[nexus-spatial-discovery]] 中 [[XR-Interface-Architect]] 的设计。
## Architecture
```
OVERVIEW CANOPY
(pipeline topology)
~~~~~~~~~~~~~~~~~~~~~~~~
/ \
/ FOCUS ARC (120 deg) \
/ primary node graph work \
/________________________________\
| |
LEFT | USER POSITION | RIGHT
UTILITY | (origin 0,0,0) | UTILITY
RAIL | | RAIL
|__________________________________|
\ /
\ SHELF (below sightline) /
\ agent status, quick tools/
\_________________________ /
```
## Four Zones
| Zone | Position | Content |
|------|----------|---------|
| Focus Arc | 120°, 1.2-2.0m | Primary node graph workspace |
| Overview Canopy | above, 2.5-4.0m | Miniature pipeline topology + health heatmap |
| Utility Rails | left/right flanks | Agent library, monitoring, logs |
| Shelf | below sightline, 0.8-1.0m | Run/stop, undo/redo, quick tools |
## Three-Layer Depth System
| Layer | Depth | Content | Opacity |
|-------|-------|---------|---------|
| Foreground | 0.8-1.2m | Active panels, inspectors, modals | 100% |
| Midground | 1.2-2.5m | Node graph, connections, workspace | 100% |
| Background | 2.5-5.0m | Overview map, ambient status | 40-70% |
## Design Rationale
- 用户处于中心,信息按重要性和使用频率分层
- z-axis深度对应执行顺序input nodes 最远output nodes 最近
- 减少晕动症:所有交互发生在 0.8-2.5m 范围
- 与 [[Semantic-Zoom]] 配合实现渐进式空间复杂度
## Related Concepts
- [[Semantic-Zoom]]:与 Command Theater 配合的导航范式
- [[SpatialAIOps]]Command Theater 的应用场景
- [[Nexus-Spatial]]Command Theater 的产品实现