Ai Six Sigma Property Os

AI Six Sigma Property OS

Named property-service workflow, actors, evidence, CTQs, approval boundaries, and MVP constraints. A bounded ontology, DMAIC control plan, agent roles, gates, metrics, and rollback-ready MVP design. Every proposed state transition and CTQ has an owner, evidence source, verifier, approval gate, and control receipt. Full ERP replacement, autonomous safety or pricing decisions, and automation of undefined processes.

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

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.

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 thresholds or automation accuracy.

1. Define: set customer pain, process boundary, work-order type, SLA, CTQs, and excluded scope.
2. Measure: map each CTQ to formula, source field, owner, baseline, target, and data-quality check.
3. Analyze: for red metrics, use process bottlenecks, fishbone categories, and 5 Why until the cause can change a rule, field, SOP, training item, or threshold.
4. Improve: propose one bounded change with hypothesis, owner, rollout cohort, budget, success/guardrail metrics, and rollback trigger.
5. Control: define dashboard, alert, approval, exception, audit sample, and review cadence.
6. Define ontology objects and legal work-order transitions before assigning agent roles.
7. Give each agent a bounded input, action, output, confidence, evidence, and human gate.
8. Keep customer-facing quotes, pricing/policy changes, low-confidence dispatch, safety, compliance, privacy, payment, case closure, and disciplinary action under human approval.

Use an independent quality reviewer for closure and abnormal cases. Rollback must restore the prior rule/SOP/version without deleting work-order evidence.

Trace every agent action and dashboard metric to a field, state transition, CTQ, owner, and gate. Simulate normal, missing-data, exception, rework, and cancellation paths. Reject modules with no objective metric or safe manual fallback.

max_attempts: 2. Retry design only after changing scope, data definition, rule, or control. Stop on repeated missing baseline, unsafe transition, or NO_PROGRESS; escalate the decision to the accountable operator.

Persist {run_id, status, attempt, budget, evidence, unknowns, last_error, next_action} plus process version, ontology, state machine, CTQ dictionary, agent contracts, approval matrix, experiment cohort, exceptions, independent review, and rollback receipt.

Failure Protocol

• NEEDS_INPUT: owner, service standard, safety boundary, or data source is unclear.
• INSUFFICIENT_EVIDENCE: baseline cannot support threshold or automation decisions.
• BLOCKED_PERMISSION: required approval/system access is absent; remain in manual mode.
• VERIFY_FAILED: state, metric, or agent action is not traceable; block rollout.
• NO_PROGRESS: two changed designs fail the same control. max_attempts: 2.
• BUDGET_STOP: preserve the manual workflow and return the smallest measurable MVP.

Output Contract

Return status, result (DMAIC memo, ontology, states, CTQs, agent/gate matrix, dashboard, MVP), evidence, unknowns, and next_action with approval and rollback condition.

Edge Cases

• Quote automation has no reliable material-cost feed: generate an internal draft with uncertainty and require human pricing approval; do not send it.
• Worker recommendation is high-confidence but violates access/safety rules: rules override score and the case moves to exception review.

Success Metrics

• One bounded workflow is measurable end to end.
• Every automated action maps to state, evidence, CTQ, owner, and human gate.
• Red metrics produce controlled countermeasures rather than commentary.

Quality Gates

• [ ] MVP excludes unrelated ERP/marketplace/payroll scope.
• [ ] CTQs have formulas, source fields, baselines, and owners.
• [ ] Independent review, approval, manual fallback, and rollback are explicit.
• [ ] Exception and rework paths were simulated.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Mark393295827
• Source: Mark393295827/third-brain-v7-skills
• License: MIT
• Homepage: https://github.com/Mark393295827/third-brain-v5-skills/tree/master

Install and usage instructions live in the source repository linked above.