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talvola

bar-assistant-mcp

by talvola

bar_favorite_cocktails

Retrieve a user's favorite cocktails by user ID to display or manage their preferred drinks.

Instructions

Get user's favorite cocktails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It implies a read, but says nothing about whose favorites are returned, whether the list is paginated, or what happens if the user has no favorites. An output schema exists, which lightens the return-value burden, but the authorization/scope behavior remains opaque.

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 short sentence with no filler and the action front-loaded. It avoids padding, but the extreme brevity is under-specification rather than efficient structure.

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

Completeness2/5

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

With an output schema present, return values need not be described, but the tool still leaves key context unstated: the meaning of user_id and its default, and whether this is a per-user or global favorites list. For a 1-parameter tool with zero annotation and zero schema coverage, the description is too thin.

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

Parameters2/5

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

Schema description coverage is 0% for the single user_id parameter, so the schema gives an agent only a name, type, and a suspicious default of 1. The description does not explain that user_id identifies the user whose favorites are fetched, nor what default 1 means (e.g., current user). It adds no meaning beyond the schema and does not compensate for the coverage gap.

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 and resource ("Get user's favorite cocktails"), which is distinct from siblings like bar_list_cocktails or bar_makeable_cocktails. However, it does not distinguish itself from siblings explicitly, and "favorite" is ambiguous (a curated list vs. per-user favorites) — the presence of a user_id parameter hints at the latter but this is left to inference.

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?

No guidance on when to use this tool versus the many sibling listing tools (bar_list_cocktails, bar_get_collection, bar_search_cocktails). No exclusions, no prerequisites, no mention of whether a user must be authenticated or how favorites are established.

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