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Pairing Guide

pairing_guide

Find beer and food pairings by searching beer styles or dish names. Get suggestions based on complement, contrast, and cleanse principles for optimal flavor combinations.

Instructions

Get beer and food pairing suggestions. Search by beer style or dish name. Returns pairing matches with complement, contrast, and cleanse principles.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesBeer style or dish name to find pairings for
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the tool's behavior by stating it 'Returns pairing matches with complement, contrast, and cleanse principles,' which adds useful context about the output format. However, it does not cover other behavioral aspects like rate limits, authentication needs, or error handling, leaving some gaps.

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 appropriately sized and front-loaded, consisting of two sentences that efficiently convey the tool's purpose, usage, and output without any wasted words. Every sentence earns its place by providing essential information.

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 the tool's low complexity (1 parameter, no output schema, no annotations), the description is mostly complete. It covers purpose, usage, and output principles, but lacks details on behavioral traits like error handling or limitations. Without an output schema, it could benefit from more specifics on return values, though the mention of 'pairing matches' provides some guidance.

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?

The schema description coverage is 100%, so the schema already documents the single parameter 'query' adequately. The description adds marginal value by clarifying that the query can be for 'beer style or dish name,' which slightly enhances understanding beyond the schema's description. With 0 parameters beyond the schema, this meets the baseline expectation.

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 clearly states the tool's purpose with specific verbs ('Get beer and food pairing suggestions') and resources ('beer style or dish name'), distinguishing it from sibling tools like 'diagnose_off_flavour' or 'suggest_recipe' by focusing on pairing recommendations rather than diagnosis, water matching, ingredient/style searches, or recipe suggestions.

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 provides clear context for when to use this tool ('Search by beer style or dish name'), but does not explicitly state when not to use it or name alternatives among the sibling tools. It implies usage for pairing queries but lacks explicit exclusions or comparisons to other tools.

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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