第 2 层 · CONNECT · 四层架构

关联

是集群,不是孤立的模型——54 个智能体,同一底座。

关联是原始信号成为智能的地方。当事件与实体、战役和既有知识链接时,它们才获得意义。这项工作由一个专业智能体集群完成——每个智能体能力面很窄,合在一起覆盖很宽的面。注册表是真实的:54 个智能体,机器可读。

查看实时图谱/api/swarm →
L2 · PROOF注册表构成
Agents in registry
real topology
Registry edges
co-membership + hubs
Domains
strategy → operations
Honeypot events
what they correlate
L2 · HOW集群如何工作
A

Specialisation is the point

Agents are categorised by domain (strategy, intelligence, security, engineering, operations) and tier (fast, smart, deep). A fast-tier agent triages; a deep-tier agent adjudicates. Routing by competence beats one model doing everything mediocrely.

B

Topology you can check

The graph on /swarm.html is not decoration — nodes and edges come from the real agent registry (domain co-membership plus cross-domain hub links), served machine-readable from /api/swarm. Click a node to read what the agent actually does.

C

Threads over chat

Agents coordinate through threads bound to root events, with summaries and status — shared memory rather than ephemeral chat. Outputs are structured so downstream agents (and auditors) consume them without re-reading prose.

D

Agent-native by design

The whole platform speaks to machines: a well-known manifest at /.well-known/agent-manifest.json, llms.txt for LLM readers, and JSON endpoints for every published figure. Agents are first-class readers of this site.

L2 · NEXT关联的下游去向
→ L3

Reasoning layer

Correlated signal becomes judgement in OpenMythos.

→ layer 03 · reason
→ visual

Live swarm graph

Interactive force-directed real topology with D1 liveness.

→ /swarm
→ register

Agent registry

Full filterable registry with manifests and run history.

→ /agents