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chrischall

myhotlunchbox-mcp

by chrischall

mhlb_get_menu

Read-only

Retrieve a student's orderable lunch menu for a specific date, including vendor, items, sizes, add-ons, prices, and the ordering deadline, so you can decide what to order.

Instructions

Get the orderable menu for one student on one date — the vendor, items, sizes, add-ons, prices and the ordering deadline. This is the read half of placing an order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateYesThe lunch date (YYYY-MM-DD).
studentIdYesStudent id from mhlb_list_students.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.0
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observedv0.2.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description need not repeat safety. It adds useful context about what is returned (orderable menu, prices, deadline) and its role in ordering, but does not disclose any additional behavioral constraints such as deadline enforcement, data availability, or error behavior. This is adequate but not rich.

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 with no filler. The first sentence front-loads the action and key data points; the second provides the workflow context. Every word contributes to the agent's understanding.

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?

Given no output schema, the description compensates by listing the major return categories and clarifying the tool's place in the order flow. It does not mention error conditions or the exact output format, but for a read-only, two-parameter menu lookup the provided detail is largely sufficient.

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 100%, so the schema already documents both parameters: date as the lunch date and studentId as sourced from mhlb_list_students. The description's 'one student on one date' merely restates the parameter scoping without adding format or dependency details. Baseline 3 applies.

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 opens with 'Get the orderable menu for one student on one date' — a specific verb and resource — then enumerates the returned contents (vendor, items, sizes, add-ons, prices, ordering deadline). It also notes this is the read half of placing an order, clearly differentiating it from order creation and other menu-adjacent tools like mhlb_get_day or mhlb_get_order_form.

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 phrase 'This is the read half of placing an order' gives clear contextual guidance: this tool should be used before any order creation or update. It does not explicitly name alternative tools or exclusion conditions, but the context is unambiguous for an agent navigating the ordering workflow.

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