Skip to main content
Glama

cooking_pair_beverages

Read-onlyIdempotent

Get wine, beer, cocktail, or non-alcoholic drink pairings for a recipe or cuisine. TRIGGERS:

  • 'what wine goes with X', 'beer pairing for X', 'drink pairing'

  • 'cocktail for dinner', 'non-alcoholic pairing', 'beverage suggestion'

  • 'wine for pasta', 'what to drink with steak'

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dishYesDish or cuisine to pair beverages with (e.g. 'grilled steak', 'Thai curry', 'seafood pasta')
beverageTypeNoType of beverage pairingall

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is established. The description adds that the input is a recipe or cuisine, but does not disclose any additional behavioral traits such as return format or number of pairings. Since annotations cover the main safety aspects, a score of 3 is appropriate.

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?

The description is concise and well-structured: a single-purpose first sentence followed by a useful TRIGGERS list. Every line adds value, and there is no redundant or filler content.

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 simple two-parameter tool with annotations and a clear purpose, the description is largely complete. However, with no output schema, it does not describe what the return value looks like (e.g., list of pairing suggestions, whether they include descriptions). A short note on output format would make it fully complete.

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%; both 'dish' and 'beverageType' already have clear descriptions and an enum for beverageType. The tool description adds no parameter-specific meaning beyond the schema, so it meets the baseline but does not exceed it.

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 a specific verb and resource: 'Get wine, beer, cocktail, or non-alcoholic drink pairings for a recipe or cuisine.' It clearly differentiates from sibling tools like substitutions and tips by listing the exact beverage types and the pairing focus.

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 TRIGGERS section provides explicit example queries for when to use this tool, such as 'what wine goes with X' and 'non-alcoholic pairing'. This gives clear positive usage context, though it does not mention when not to use it or explicitly name alternatives.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources