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solve_employee_shift_scheduling

Optimally assign employees to shifts across multiple days, respecting individual constraints and preferences, to generate balanced schedules and coverage statistics.

Instructions

Solve Employee Shift Scheduling to assign employees to shifts optimally.

    Args:
        employees: List of employee names
        shifts: List of shift dictionaries with time and requirements
        days: Number of days to schedule
        employee_constraints: Optional constraints and preferences per employee
        time_limit_seconds: Maximum solving time in seconds (default: 30.0)

    Returns:
        Optimization result with employee schedules and coverage statistics
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
employeesYes
shiftsYes
daysYes
employee_constraintsNo
time_limit_secondsNo
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description should disclose behavioral traits. It mentions optimality and a time limit default of 30 seconds, but does not explain the optimization method, constraints impact, side effects, or computational complexity. The behavior is vaguely described.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured as a docstring with Args and Returns sections, which is readable. However, it could be more concise by removing redundancy (e.g., repeats 'Optional' in the default value comment). Overall adequate but not exemplary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 5 parameters with 0% coverage, the description should cover more. It mentions return value vaguely ('Optimization result with employee schedules and coverage statistics') and does not explain constraint details or error handling. The description is insufficient for full understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description must add meaning. It lists parameters with brief explanations (e.g., 'List of employee names', 'List of shift dictionaries with time and requirements'), but lacks details on expected keys for shifts or the format of employee_constraints. It adds some value beyond the schema but is incomplete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it solves employee shift scheduling to assign employees to shifts optimally. This distinguishes it from sibling tools like solve_job_shop_scheduling or solve_vehicle_routing_problem, which address different scheduling problems.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives such as solve_assignment_problem_tool or solve_job_shop_scheduling. It does not mention prerequisites, limitations, or scenarios where this tool is preferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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