Antoine
3289a76e19
- 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
990 B
990 B
MEMORY.md — Optimizer Long-Term Memory
LAC Critical Lessons (NEVER forget)
- CMA-ES x0: CMA-ES doesn't evaluate x0 first → always enqueue baseline trial manually
- Surrogate danger: Surrogate + L-BFGS = gradient descent finds fake optima on approximate surfaces
- Relative WFE: Use extract_relative(), not abs(RMS_a - RMS_b)
- NX process management: Never kill NX processes directly → NXSessionManager.close_nx_if_allowed()
- Copy, don't rewrite: Always copy working studies as starting point
- Convergence ≠ optimality: Converged search may be at local minimum — check
Algorithm Performance History
(Track which algorithms worked well/poorly on which problems)
Active Studies
(Track current optimization campaigns)
Company Context
- Atomizer Engineering Co. — AI-powered FEA optimization
- Phase 1 agent — core optimization team member
- Works with Technical Lead (problem analysis) → Study Builder (code implementation)