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Generate an employee schedule

rotase_generate_schedule
Read-onlyIdempotent

Generate a monthly employee schedule from a complete Rotase project payload. Use rotase_examples to obtain a template, then rotase_validate_project first. The operation calculates and returns a schedule; it does not save a project, modify browser storage or create an account. Explain returned violations or shortages instead of assuming that every project is schedulable.

Input Schema

NameRequiredDescriptionDefault
storeYes
projectYes
employeesYes
schedulesNo
preferencesNo
availabilityNo
schemaVersionNo
monthlyTargetsNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered; the description still adds value by spelling out the negative side effects (no project save, no browser-storage mutation, no account creation) and by warning that output may contain violations or shortages. It stops short of describing determinism, cost, or pagination, so it is strong but not exhaustive.

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

Conciseness4/5

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

Three sentences, each doing distinct work: purpose, prerequisite workflow, and side-effect/output caveats, with the core action front-loaded. Slightly dense in the final warning sentence, but no filler.

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

Completeness4/5

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

For a complex, nested-input tool with an output schema (so return values need not be explained), the description covers purpose, prerequisites, and side-effect boundaries. The missing piece is any orientation to the payload's constituent parts, which matters given eight undocumented parameters.

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

Parameters2/5

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

With eight parameters, three required, nested objects, and 0% per-parameter schema coverage, the description only gestures at 'a complete Rotase project payload' and never explains store, employees, schedules, preferences, availability, schemaVersion, or monthlyTargets. The root object description in the schema carries the required/optional distinction, but the tool description itself contributes essentially no parameter meaning.

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?

States a specific verb and resource ('Generate a monthly employee schedule') plus the required input ('complete Rotase project payload'), so the agent knows exactly what the tool produces. It also implicitly separates itself from rotase_validate_project and rotase_examples by casting them as prerequisite steps rather than alternatives.

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

Usage Guidelines5/5

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

Gives an explicit ordered workflow ('Use rotase_examples to obtain a template, then rotase_validate_project first') and states when-not-to-expect-something ('does not save a project'), which is exactly the routing guidance an agent needs. Nothing about sequencing is left to inference.

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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