Rotawise Shift Scheduler

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

Beyond the safe annotations, the description details the exact checks performed (overlapping, rest, max hours), the return types (PDF, Excel, calendars), and crucial behavioral constraints (no legal advice, no mutation). This provides exhaustive context on the tool's operational limits.

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

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

The definition is quite lengthy, which detract from absolute conciseness. However, every sentence serves a purpose, and the structure efficiently organizes functional requirements and limitations without any wasted language.

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

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

Given the complexity and the high parameter count, the definition is highly complete. It covers input formats, all key functional logic, output formats, and operational boundaries, leaving no major functional gap for an agent.

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

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

While the schema is 100% covered, the description adds vital semantic context. It explains input variations, such as that the staff data can be typed, or supplied via a CSV/XLSX grid or list. It also provides functional definitions for complex rules like 'clopening'.

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

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

The tool's purpose is perfectly clear: it checks a schedule against scheduling rules. Furthermore, it distinguishes itself explicitly from the sibling tool, generate_shift_schedule, by stating it 'Does not change the schedule itself'.

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

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

The description provides clear use cases and examples ('clopening', 'over 40 hours'). It effectively guides the user by contrasting its function (checking) with the function of its sibling tool (generating/fixing).

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

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

The description adds substantial context beyond the annotations: it explains the deterministic solver, which hard rules are checked, fairness balancing, what happens when coverage is impossible, and the output formats. It also clarifies operational boundaries such as not posting schedules, messaging staff, tracking clock-ins, or running payroll, consistent with the read-only and non-destructive annotations.

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

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

The description is front-loaded with the primary use case and examples before moving into solver behavior, outputs, and exclusions. It is long but dense with relevant information for a complex scheduling tool, with little repetition, though the example list could be trimmed slightly without losing clarity.

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

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

Given the tool's complexity, nested schema, and output schema, the description is complete enough for an agent to invoke it confidently. It covers inputs, solver behavior, edge cases like overnight shifts and daylight-saving weeks, output artifacts, and explicit non-goals.

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

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

Schema description coverage is 100%, so the schema already documents all 11 parameters in detail. The description reinforces major input categories such as staff, roles, availability, min/max hours, shifts, and attached CSV/XLSX files, but does not add syntax or constraints beyond what the schema already provides. Baseline 3 is appropriate when the schema carries the parameter documentation.

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

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

The description states a specific verb and resource: build a weekly staff or shift schedule from staff, availability, hour limits, and shift coverage. It explicitly distinguishes itself from check_schedule and rules out job searches and payroll-related tasks, so an agent can identify its purpose without opening the schema.

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

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

It gives explicit when-to-use guidance with several concrete user scenarios, including examples like "make a weekly schedule for 6 employees" and "Sam cannot work Mondays." It also states when not to use it and points to check_schedule for checking an existing schedule.

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