Shift Schedule Builder Skill

A schedule is a bet on demand: overstaff and you burn margin, understaff and service (and your best people) walk. This skill builds coverage from the demand curve out — enough hands at the rush, lean in the lulls — then checks the labor cost and the human constraints before it's posted.

Working from a brief

Given the team, hours, and demand pattern, produce the full schedule — infer the day-part demand shape from the business type if no forecast is given (label it). Respect stated availability and time-off; never schedule someone into a conflict you were told about.

Required Inputs

Ask for (if not provided, else infer and label):

• Team — names/roles, pay rates or an average, and availability/time-off
• Operating hours and the demand pattern (covers by day-part, peak times, events)
• Labor-cost target (% of revenue or a dollar cap) and any rules (max hours, required rest, minors)

Output Format

Coverage plan

Demand mapped to required heads per role per day-part:

| Day-part | Forecast demand | Cooks | Servers | Support | Notes | |---|---|---|---|---|---|

The schedule

Person-by-person shifts across the week (start–end, role, station), with total hours per person.

Labor cost check

Projected labor hours × rates → labor cost, as a % of forecast revenue vs. the target, with the gap and where to trim/add.

Guardrails flagged

Overtime risk, insufficient rest between close/open ("clopening"), availability conflicts, minor-hour limits, and anyone over/under their expected hours.

Quality Checks

• ] Staffing per day-part is driven by the demand pattern, not flat coverage
• ] Projected labor cost is computed and compared to the target
• ] No one is scheduled against stated availability or time-off
• ] Rest-between-shifts, overtime, and minor-hour rules are checked and flagged
• ] Hours are distributed with an eye to fairness, not just cost

Anti-Patterns

• Flat staffing that ignores the rush-and-lull demand curve
• Posting a schedule without checking the labor-cost %
• Scheduling "clopens" or overtime by accident
• Ignoring stated availability (the fastest way to lose staff)
• Cutting so lean that service and food quality collapse at peak