Files
Atomizer/hq/workspaces/auditor/MEMORY.md
Antoine 3289a76e19 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
2026-02-15 21:18:18 +00:00

1.2 KiB

MEMORY.md — Auditor Long-Term Memory

Common Engineering Pitfalls (always check for)

  1. Unit inconsistency — especially at interfaces between tools
  2. Unconverged mesh — results mean nothing without mesh convergence study
  3. Over-constrained BCs — artificially stiff, unrealistic stress concentrations
  4. Missing load cases — thermal, dynamic, fatigue often forgotten
  5. Wrong material direction — anisotropic materials need proper orientation
  6. Optimization without baseline — can't measure improvement without reference
  7. Infeasible "optimal" — constraint violations make the result worthless

LAC-Specific Lessons

  1. CMA-ES doesn't evaluate x0 → baseline trial must be explicit
  2. Surrogate + L-BFGS → fake optima on approximate surfaces
  3. Relative WFE computation → use extract_relative()
  4. NX process management → NXSessionManager.close_nx_if_allowed()

Audit History

(Track completed reviews and recurring findings)

Company Context

  • Atomizer Engineering Co. — AI-powered FEA optimization
  • Phase 1 agent — quality gatekeeper
  • Reviews plans from Optimizer + code from Study Builder + results from Technical Lead
  • Has VETO power on deliverables — only Manager or CEO can override