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fliptheweb

yazio-mcp

by fliptheweb
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_user_suggested_products

Read-onlyIdempotent

Retrieve product suggestions for a user’s breakfast, lunch, dinner, or snack on a specified date, with an optional limit on results.

Instructions

Get product suggestions for the user for a meal (daytime) on a date

Input Schema

NameRequiredDescriptionDefault
dateNoDate to get suggestions for (defaults to today)
limitNoMaximum number of results to return
daytimeNoMeal to get suggestions for (defaults to breakfast)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv0.0.15
    • addedInput schema / properties / date
      Added value: +{
+  "description": "Date to get suggestions for (defaults to today)",
+  "format": "date",
+  "pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))$",
+  "type": "string"
+}
    • addedInput schema / properties / daytime
      Added value: +{
+  "description": "Meal to get suggestions for (defaults to breakfast)",
+  "enum": [
+    "breakfast",
+    "lunch",
+    "dinner",
+    "snack"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / limit / exclusiveMinimum
      Added value: +0
    • addedInput schema / properties / limit / maximum
      Added value: +9007199254740991
    • changedInput schema / properties / limit / type
      Previous value: -"number"New value: +"integer"
    • removedInput schema / properties / query
      Removed value: -{
-  "description": "Search query (optional)",
-  "type": "string"
-}
  2. First observedv0.0.12

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description adds the meal/date scoping that explains why results vary per call, but says nothing about how suggestions are generated (personalization, dietary preferences, history) or how many are returned by default.

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?

A single front-loaded sentence with no filler. Slight deduction because 'for the user for a meal (daytime) on a date' is redundantly worded and could be tightened.

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

Completeness3/5

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

This is a simple read tool with full schema coverage and no output schema, so a short description is defensible. However, an agent still lacks any sense of what a 'suggestion' is (personalized? ranked? filtered by dietary preferences?) and how it differs from the sibling search_products.

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 description coverage is 100%, including enum values for daytime and a pattern for date, so the schema carries the parameter burden. The description restates 'meal (daytime)' and 'date' but adds no new semantics and never mentions the limit parameter or default behaviors beyond what the schema already documents.

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 names a specific verb ('Get') and resource ('product suggestions') and scopes it by meal and date. It is clear what the tool returns, but it never distinguishes itself from the close sibling search_products, which an agent could easily mistake for the same operation.

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

Usage Guidelines3/5

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

Usage is only implied: an agent can infer this is for per-meal recommendations rather than generic product lookup, but there is no explicit when-to-use, no when-not-to-use, and no mention of search_products as the alternative for free-form product lookup.

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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