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oliverhruby

EduPage MCP Server

by oliverhruby
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

rate_meal

DestructiveIdempotent

Submit quality and quantity ratings for a specified date and meal type to record school meal feedback.

Instructions

Rate a meal. Writes: submits quality/quantity ratings for a date and meal type.

Args: date_str: YYYY-MM-DD of the meal. meal_type: 'snack' | 'lunch' | 'afternoon_snack'. quality: Taste rating, 1-5. quantity: Portion-size rating, 1-5. subdomain: School to query (defaults to the active subdomain).

Returns: dict: {'rated': True, meal_type, date}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qualityYes
date_strYes
quantityYes
meal_typeYes
subdomainNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.6.0
    • addedInput schema / properties / subdomain / anyOf
      Added value: +[
+  {
+    "type": "string"
+  },
+  {
+    "type": "null"
+  }
+]
    • removedInput schema / properties / subdomain / type
      Removed value: -"string"
  2. First observedv0.4.6

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare the write/destructive/idempotent nature, and the description adds the return format and parameter details. However, it does not elaborate on what 'destructive' means (e.g., overwriting an existing rating) or confirm idempotency, so it adds only modest context beyond annotations.

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?

The description is front-loaded with a clear summary and then structured into Args and Returns sections. It is appropriately sized for a 5-parameter tool with no schema descriptions, though 'Writes:' is slightly redundant with 'Rate a meal'.

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 provides the return shape, and it documents all parameters thoroughly. It could mention overwrite behavior or permissions, but with annotations covering safety and a clear action, it is largely complete.

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

Parameters4/5

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

Schema description coverage is 0%, so the description carries the full burden. It defines all five parameters with format and meaning: date_str as YYYY-MM-DD, meal_type with enumerated values, quality and quantity as 1-5 scales, and subdomain defaulting to the active subdomain. This is thorough.

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

Purpose4/5

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

The description states a specific verb and resource: 'Rate a meal' and clarifies it writes quality/quantity ratings for a date and meal type. It does not explicitly differentiate from sibling tools like choose_meal or sign_off_meal, but the purpose is clear.

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?

There is no guidance on when to use this tool versus alternatives such as get_meals, choose_meal, or sign_off_meal. The description only implies usage through the name and action, leaving the agent to infer.

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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