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Shift Scheduler

Get an example roster input

get_shift_example
Read-only

Return the full input JSON of one example, in exactly the shape build_shift_roster accepts. Edit it (names, days, headcounts, rules) to match the user's situation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoes = Spanish shift and post names.
nameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true and destructiveHint=false, and the description adds useful behavioral context: the return value is a full input payload in build_shift_roster's exact shape, and it is meant to be edited before use. It does not contradict the annotations.

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

Conciseness5/5

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

Two sentences, zero filler. The first sentence front-loads the exact behavior and output shape; the second gives actionable guidance. Every sentence earns its place.

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

Completeness5/5

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

The tool is low-complexity, has read-only annotations, enum-only parameters, and no output schema. The description gives agents everything needed to call it correctly and understand what the response will be: one full example JSON shaped for build_shift_roster.

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?

The schema documents both parameters with enums, and lang has its own description, so parameter meaning is mostly covered by structured data. The description does not add meaning to the name selector, though the enum values are self-explanatory. It adds editing guidance about fields inside the example, not about the parameters themselves.

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 states a specific verb ('Return') and resource ('full input JSON of one example'), and it distinguishes the tool from siblings by explicitly tying the output shape to build_shift_roster. There is no ambiguity about what the tool does.

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

Usage Guidelines4/5

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

The description clearly implies when to use it: when the agent needs a concrete, editable example to adapt for the user's situation. It does not explicitly mention when not to use it or contrast it with list_shift_examples, which keeps it from a 5.

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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