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
26 lines
1.2 KiB
Markdown
26 lines
1.2 KiB
Markdown
# MEMORY.md — Auditor Long-Term Memory
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## Common Engineering Pitfalls (always check for)
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1. **Unit inconsistency** — especially at interfaces between tools
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2. **Unconverged mesh** — results mean nothing without mesh convergence study
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3. **Over-constrained BCs** — artificially stiff, unrealistic stress concentrations
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4. **Missing load cases** — thermal, dynamic, fatigue often forgotten
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5. **Wrong material direction** — anisotropic materials need proper orientation
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6. **Optimization without baseline** — can't measure improvement without reference
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7. **Infeasible "optimal"** — constraint violations make the result worthless
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## LAC-Specific Lessons
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1. CMA-ES doesn't evaluate x0 → baseline trial must be explicit
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2. Surrogate + L-BFGS → fake optima on approximate surfaces
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3. Relative WFE computation → use extract_relative()
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4. NX process management → NXSessionManager.close_nx_if_allowed()
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## Audit History
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*(Track completed reviews and recurring findings)*
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## Company Context
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- Atomizer Engineering Co. — AI-powered FEA optimization
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- Phase 1 agent — quality gatekeeper
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- Reviews plans from Optimizer + code from Study Builder + results from Technical Lead
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- Has VETO power on deliverables — only Manager or CEO can override
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