feat: add Atomizer HQ multi-agent cluster infrastructure

- 8-agent OpenClaw cluster (Manager, Tech-Lead, Secretary, Auditor,
  Optimizer, Study-Builder, NX-Expert, Webster)
- Orchestration engine: orchestrate.py (sync delegation + handoffs)
- Workflow engine: YAML-defined multi-step pipelines
- Agent workspaces: SOUL.md, AGENTS.md, MEMORY.md per agent
- Shared skills: delegate, orchestrate, atomizer-protocols
- Capability registry (AGENTS_REGISTRY.json)
- Cluster management: cluster.sh, systemd template
- All secrets replaced with env var references

hq/workspaces/manager/memory/2026-02-11.md

@@ -0,0 +1,29 @@
+# 2026-02-11
+
+## Channel Config
+- Added #research-and-development (C0AEB39CE5U) to Slack config
+- All 6 agents bound to it
+- Set `requireMention: false` globally for all Slack channels per Antoine's request
+
+## NXOpen MCP Server — INSTALLED ✅
+- **Repo**: `http://100.80.199.40:3000/Antoine/NXOpen-MCP.git`
+- **Local path**: `/home/papa/atomizer/tools/nxopen-mcp/`
+- **Venv**: `.venv/` with CPU-only torch (no CUDA needed)
+- **Data**: 203MB pre-indexed ChromaDB + JSON caches
+  - 15,219 NXOpen classes, 64,320 methods
+  - 149 nxopentse functions
+  - 287 pyNastran classes
+- **Run**: `./run-server.sh` or `python -m nxopen_mcp.server --data-dir ./data`
+- **Protocol**: stdio-based MCP
+- **Tools**: search_nxopen, get_class_info, get_method_info, get_examples, list_namespaces
+- Wired into NX Expert agent via exec/Python subprocess
+
+## NX Expert Agent — HIRED ✅
+- **Agent ID**: `nx-expert`
+- **Model**: Sonnet 4 (cost-effective specialist)
+- **Workspace**: `/home/papa/atomizer/workspaces/nx-expert/`
+- **Channels**: #hq (C0AEJV13TEU), #research-and-development (C0AEB39CE5U)
+- **Mention patterns**: @nx-expert, @NX Expert, @nx, 🖥️
+- **Tools**: NXOpen MCP via Python exec, atomizer-protocols skill
+- **Role**: NX Open API expert, solver config, element selection, journal scripting
+- First Phase 2 agent to come online — ahead of schedule