# Forge Industrial Intelligence Pack — Schema

One row = one complete operational scenario lifecycle. All records share the same fourteen top-level fields.

Schema version: `1.0.0-forge-industrial-sample`

## Top-level fields

### `schema_version` — string
Schema identifier. Constant within a sample release.

### `event` — struct
Identifier fields and the overall status/severity for the lifecycle.

| Field | Type | Notes |
|---|---|---|
| `id` | string | Stable event identifier, e.g., `FORGE-100000`. |
| `trace_id` | string (UUID) | Cross-links telemetry within the lifecycle. |
| `timestamp` | string (ISO-8601) | Scenario anchor time. |
| `scenario` | string | One of: `port_spillover_surge`, `power_constrained_ev_yard`, `labor_gap_service_degradation`, `cold_chain_excursion_risk`, `tenant_hypergrowth_overrun`, `last_mile_cutoff_compression`, `site_selection_power_arbitrage`. |
| `severity` | string | `medium`, `high`, `critical`. |
| `status` | string | `decision_pending`, `triaged`, `confirmed`. |
| `confidence` | double | 0–1 confidence of the event label. |

### `organization` — struct
Market-level context for the facility/portfolio.

| Field | Type | Notes |
|---|---|---|
| `sector` | string | Always `industrial_real_estate`. |
| `market` | string | Generic submarket archetype (e.g., `Dallas-Fort Worth`, `Los Angeles`, `Chicago`, `Atlanta`, `New Jersey`, `Phoenix`). Used as a type-label, not a specific-property reference. |
| `submarket` | string | Submarket handle (e.g., `Inland Port`, `Inland Empire`, `Joliet`, `West Valley`). |
| `region` | string | Regional bucket (`south_central_us`, `west_coast_us`, etc.). |
| `environment` | string | Deployment bucket (e.g., `production_portfolio`). |
| `port_proximity_km` | int | Proximity to major port, km. |
| `airport_proximity_km` | int | Proximity to major airport, km. |
| `highway_access_score` | double | 0–1. |
| `labor_tightness` | double | 0–1. |
| `grid_headroom_mw` | double | Available grid capacity (MW). |
| `industrial_vacancy_pct` | double | Submarket vacancy rate (percent). |
| `base_rent_psf_yr` | double | Submarket base rent ($/sqft/yr). |
| `population_density` | int | People per sq km. |
| `development_cycle_days` | int | Typical time-to-delivery for spec construction. |

### `identity_context` — struct
Decision owner and authorization lineage.

| Field | Type | Notes |
|---|---|---|
| `principal_id` | string | Synthetic identity handle (e.g., `ops://tnt-XXX/node/fac-YYY`). |
| `decision_lineage` | list<struct> | Ordered `role` / `action` / `authority_level` entries showing the approval chain. |
| `auth_method` | string | How the decision was authenticated (e.g., `tower_dashboard`). |
| `is_automated_recommendation` | bool | Whether the decision started as an automated rec. |
| `stakeholder_latency_hours` | int | Hours of stakeholder lag. |
| `meeting_load` | string | `low` / `moderate` / `high`. |

### `vulnerability` — struct
Risk taxonomy and severity vector.

| Field | Type | Notes |
|---|---|---|
| `class` | string | Scenario-class label (same as `simulation.ground_truth_label`). |
| `risk_taxonomy` | list<string> | Ordered taxonomy codes (e.g., `LOG-LOC-001`, `LOG-DEM-004`). |
| `exposure` | string | Primary exposure dimension (e.g., `demand_pressure`, `service_risk`). |
| `severity_model.base_score` | double | 0–10 severity base. |
| `severity_model.vector` | string | Vector string encoding severity dimensions (e.g., `LOG:3.1/EX:O/FR:C/...`). |

### `tenant_context` — struct
Synthetic tenant profile tied to this scenario.

| Field | Type | Notes |
|---|---|---|
| `tenant_id` | string | Synthetic tenant identifier (e.g., `TNT-189FCA4461`). |
| `industry` | string | `ecommerce`, `3pl`, `retail_distribution`, `cold_chain`, `industrial_manufacturing`. |
| `truck_profile` | string | `parcel_heavy`, `mixed_freight`, `palletized`, `reefer`, `inbound_component`. |
| `order_growth_rate` | double | Growth rate delta. |
| `sqft_footprint` | int | Facility sqft. |
| `expansion_open` | bool | Whether the tenant is open to expanding. |
| `retention_priority` | string | `standard`, `high`, `strategic`. |
| `risk_of_churn` | double | 0–1 churn risk. |

### `facility_context` — struct
Building-level attributes: capacity, energy, clear heights, dock counts, refrigeration, automation level.

### `portfolio_context` — struct
Network-level dynamics: submarket share, adjacent-node capacity, cross-site elasticity.

### `telemetry_stream` — list<struct>
Variable-length ordered telemetry readings representing the evolving system state across the scenario. Each element includes an event-name label matching one item in the scenario's event sequence, plus relevant signal readings (dock utilization, queue length, power load, service commitment risk, truck turn time, temperature delta, etc.).

### `detection` — struct
Anomaly-signature metadata.

| Field | Type | Notes |
|---|---|---|
| `analytic_family` | string | Analytic family label (e.g., `industrial_real_estate_behavioral_intelligence`). |
| `primary_risk_class` | string | Primary risk dimension. |
| `rule_logic` | string | SQL-like rule expression for the detector. |
| `baseline_deviation` | string | Short English description of the deviation pattern. |
| `anomaly_score` | double | 0–1. |
| `confidence_band` | string | `low` / `medium` / `high` / `very_high`. |
| `forecast_pressure_delta` | double | Delta vs baseline forecast. |
| `signal_conflicts` | list<string> | Conflicting signal labels, if any. |

### `forecast` — struct
Forward-looking predictions tied to this scenario: demand shift, occupancy trajectory, pricing outlook.

### `impact` — struct
Economic consequences: revenue delta, NOI impact, capex required, churn risk delta.

### `response` — struct
Recommended actions and execution context.

| Field | Type | Notes |
|---|---|---|
| `recommended_actions` | list<string> | Top actions ranked by score. |
| `primary_action` | string | Selected action (e.g., `shift_overflow_to_satellite`). |
| `primary_action_score` | double | Scoring metric for the primary action. |
| `primary_action_reason` | string | Short reason code. |
| `alternative_actions` | list<struct> | `action` / `score` / `reason` triples. |
| `decision_owner` | string | Role who owns the decision (e.g., `operations_lead`, `market_officer`, `development_committee`). |
| `execution_window_days` | int | Execution SLA. |
| `playbook_id` | string | Synthetic playbook identifier, prefixed `FORGE-PB-`. |
| `capex_gate_required` | bool | Whether capex approval is required. |
| `stakeholders` | list<string> | Additional stakeholder roles. |
| `expected_operational_outcome` | string | `partial_success`, `success`, `mitigation`, etc. |
| `recommended_tradeoff` | string | Short tradeoff description (e.g., `preserve_capital_with_higher_latency_risk`). |
| `execution_risk_band` | string | `low`, `moderate`, `elevated`, `high`. |

### `simulation` — struct
Simulation engine provenance and ground-truth labels.

| Field | Type | Notes |
|---|---|---|
| `synthetic` | bool | Always `true`. |
| `engine` | string | Simulation engine label (`forge_industrial_sim_v1`). |
| `causal_coherence` | string | Coherence mode descriptor (e.g., `rich_schema_with_balanced_policy`). |
| `friction_profile` | struct | Numeric friction dimensions: `budget_pressure`, `labor_shortage`, `power_stress`, `demand_pressure`, `service_risk`, `portfolio_tightness`, `capital_availability`, `entitlement_friction`, `weather_disruption`, `upside_mode` (bool). |
| `ground_truth_label` | string | Scenario class (e.g., `Network_Optimization`, `Labor_Constraint`, `Temperature_Control_Risk`). |
| `intended_use` | list<string> | ML use-case tags (e.g., `forecasting`, `site_selection`, `tenant_expansion_decisions`). |

## Distribution of this sample

- 10,000 lifecycles total.
- Severity: balanced across `medium` / `high` / `critical` (~3,300 each).
- Status: balanced across `decision_pending` / `triaged` / `confirmed` (~3,300 each).
- Scenario: balanced across 7 scenario classes (~1,400 each).
- Market: balanced across 6 submarket archetypes (~1,600 each).
- Industry: balanced across 5 tenant archetypes (~2,000 each).

## Sanitization notes

- Internal identifier prefix (`PLG-REAL-*`) has been normalized to `FORGE-*`.
- Internal playbook prefix (`PLG-PB-*`) has been normalized to `FORGE-PB-*`.
- Internal engine label (`SIMA-inspired industrial reality generator`) has been normalized to `forge_industrial_sim_v1`.
- Market names (Dallas-Fort Worth, LA, Chicago, Atlanta, NJ, Phoenix) are used as submarket archetypes for industrial-real-estate type labels, not specific property or operator references.
- No real facility telemetry, real tenant identities, real portfolio NOI, or identifiable stakeholder data are present.

## Relationship to the full pack

The production pack scales to 5M+ lifecycles with expanded market and submarket coverage, richer per-step telemetry, additional scenario classes (ESG signals, geopolitical supply disruption, labor automation events, bonded warehouse flows), and multi-year longitudinal traces per tenant. See the pack card for commercial access.