ai-six-sigma-property-os

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Use when property-service operations need an AI plus ontology plus DMAIC design for work orders, dispatch, quotes, evidence, CTQ metrics, and control dashboards.

AI & Automation 124 stars 18 forks Updated 3 days ago MIT

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Quality Score: 87/100

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100
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80
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Skill Content

# AI Six Sigma Property OS <skill_contract> <input>Named property-service workflow, actors, evidence, CTQs, approval boundaries, and MVP constraints.</input> <output>A bounded ontology, DMAIC control plan, agent roles, gates, metrics, and rollback-ready MVP design.</output> <done>Every proposed state transition and CTQ has an owner, evidence source, verifier, approval gate, and control receipt.</done> <non_goals>Full ERP replacement, autonomous safety or pricing decisions, and automation of undefined processes.</non_goals> Ontology defines the operating world; bounded agents execute and audit; DMAIC improves rules from work-order evidence. Design the management system before software scope. Load `references/property-control-model.md` for the baseline ontology, CTQs, and state machine. ## Usage Template Provide: business type, stage, first workflow, current process/data, service standards, approval boundaries, failure history, and MVP budget. Optional: table schemas and sample work orders. ## Workflow <intake> Verify the operating objective and select one first workflow: classification, dispatch recommendation, quote draft, evidence audit, or quality dashboard. Map actors, current states, systems of record, customer/safety impact, and data maturity. </intake> <unknowns_gate> If service standard, accountable owner, safety boundary, or system of record is missing, return `NEEDS_INPUT`. Treat absent baseline data as a Measure-phase task; never invent CTQ thresho...

Details

Author
Mark393295827
Repository
Mark393295827/third-brain-v7-skills
Created
2 months ago
Last Updated
3 days ago
Language
HTML
License
MIT

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