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
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57
hq/workspaces/shared/workflows/design-review.yaml
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57
hq/workspaces/shared/workflows/design-review.yaml
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name: Design Review
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description: Multi-agent design review pipeline
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trigger: manual
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inputs:
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design_description:
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type: text
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description: "What is being reviewed"
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requirements:
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type: text
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description: "Requirements to review against"
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steps:
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- id: technical_review
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agent: tech-lead
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task: |
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Perform a technical review of the following design:
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DESIGN: {inputs.design_description}
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REQUIREMENTS: {inputs.requirements}
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Assess: structural adequacy, thermal performance, manufacturability,
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and compliance with requirements. Identify risks and gaps.
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timeout: 300
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- id: optimization_review
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agent: optimizer
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task: |
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Assess optimization potential for the following design:
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DESIGN: {inputs.design_description}
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REQUIREMENTS: {inputs.requirements}
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Identify: parameters that could be optimized, potential weight/cost savings,
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and whether a formal optimization study is warranted.
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timeout: 300
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# These two run in PARALLEL (no dependency between them)
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- id: audit
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agent: auditor
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task: |
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Perform a final quality review combining both the technical and optimization assessments:
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TECHNICAL REVIEW:
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{technical_review}
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OPTIMIZATION REVIEW:
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{optimization_review}
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Assess completeness, identify conflicts between reviewers, and provide
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a consolidated recommendation.
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depends_on: [technical_review, optimization_review]
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timeout: 180
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notifications:
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on_complete: "Design review complete"
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58
hq/workspaces/shared/workflows/material-trade-study.yaml
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hq/workspaces/shared/workflows/material-trade-study.yaml
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name: Material Trade Study
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description: Research, evaluate, and audit material options for optical components
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trigger: manual
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inputs:
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materials:
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type: list
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description: "Materials to compare"
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requirements:
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type: text
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description: "Performance requirements and constraints"
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steps:
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- id: research
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agent: webster
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task: |
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Research the following materials: {inputs.materials}
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For each material, find: CTE (with temperature range), density, Young's modulus,
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cost per kg, lead time, availability, and any known issues for optical applications.
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Provide sources for all data.
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timeout: 180
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retries: 2
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output: material_data
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- id: evaluate
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agent: tech-lead
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task: |
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Evaluate these materials against our requirements:
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REQUIREMENTS:
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{inputs.requirements}
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MATERIAL DATA:
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{research}
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Provide a recommendation with full rationale. Include a comparison matrix.
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depends_on: [research]
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timeout: 300
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retries: 1
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output: technical_assessment
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- id: audit
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agent: auditor
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task: |
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Review this material trade study for completeness, methodological rigor,
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and potential gaps:
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{evaluate}
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Check: Are all requirements addressed? Are sources credible?
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Are there materials that should have been considered but weren't?
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depends_on: [evaluate]
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timeout: 180
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output: audit_result
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notifications:
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on_complete: "Workflow complete"
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on_failure: "Workflow failed"
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29
hq/workspaces/shared/workflows/quick-research.yaml
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hq/workspaces/shared/workflows/quick-research.yaml
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name: Quick Research
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description: Fast web research with technical validation
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trigger: manual
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inputs:
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query:
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type: text
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description: "Research question"
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steps:
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- id: research
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agent: webster
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task: "{inputs.query}"
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timeout: 120
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retries: 1
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- id: validate
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agent: tech-lead
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task: |
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Verify these research findings are accurate and relevant for engineering use:
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{research}
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Flag any concerns about accuracy, missing context, or applicability.
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depends_on: [research]
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timeout: 180
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notifications:
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on_complete: "Research complete"
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