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talvola

bar-assistant-mcp

by talvola

bar_ingredient_cocktails

Retrieve cocktails that use a specific ingredient by supplying its ID.

Instructions

Get cocktails that use a specific ingredient.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden, and it discloses nothing beyond the purpose. It does not say whether matching is exact or fuzzy, whether results are paginated or capped, or whether an unknown ingredient id errors or returns empty.

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 zero filler, which is appropriate for a one-parameter lookup. It is efficient rather than verbose, though it is arguably under-specified rather than genuinely concise.

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?

An output schema exists, so return values need not be explained, and the operation is simple with one parameter. Still, with no annotations and no usage or matching-behavior notes, an agent lacks enough to call this confidently against its many siblings.

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 0% and the single parameter is an undescribed 'id'. The description does add one useful disambiguation by stating the id refers to an ingredient (not a cocktail), but it gives no format, name-vs-id, or validation detail.

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?

States a specific verb ('Get') and resource ('cocktails that use a specific ingredient'), which is enough for an agent to know the retrieval is ingredient-driven. It does not differentiate itself from siblings such as bar_search_cocktails or bar_uses_for_bottle, so it stops short of a 5.

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 when-to-use guidance and no named alternative, despite many plausible siblings (bar_search_cocktails, bar_uses_for_bottle, bar_makeable_cocktails). The agent must infer the use case entirely from the one-line purpose.

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