forecasting-model

name	forecasting-model
description	Build and evaluate a forecast with time-aware validation, baselines, uncertainty intervals, covariates, and scenario sensitivity.

Forecasting Model

Use when this procedure is the primary professional method needed for the assignment.

Procedure

1. Confirm the decision or outcome this work must support, its scope, owner, constraints, and definition of success.
2. Establish the evidence baseline using historical series, event calendar, known future inputs, missing data, structural breaks, and decision horizon. Do not fill material gaps with assumptions when they can change the result.
3. Define horizon/granularity, establish naive baselines, split without leakage, model seasonality/drivers, compare forecast error, and communicate intervals.
4. Exercise realistic edge, failure, transition, or exception cases that could invalidate the result; record unresolved uncertainty explicitly.
5. Validate the output against the original outcome and any neighboring professional contracts so this skill does not silently absorb another specialist's authority.
6. Record the resulting artifact, measurements, decisions, provenance, and handoff information needed for another owner to reproduce or continue the work.

Quality gate

The model beats an appropriate baseline on held-out periods and uncertainty is calibrated enough for the intended decision.