Skip to main content
Glama
talvola

bar-assistant-mcp

by talvola

bar_list_methods

List cocktail preparation methods available in Bar Assistant to help users choose how to make drinks.

Instructions

List cocktail preparation methods.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
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 burden of behavioral disclosure, yet it says nothing about read-only nature, whether the results are cached or static, or any rate/permission constraints. For a zero-argument lookup the safety profile is implied but not stated.

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 wasted words. It is appropriately sized for a trivial list tool, though it is arguably too terse to earn a top score.

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?

With zero parameters and an output schema present, the description does not need to explain return values, so it is close to sufficient. However, with no annotations it leaves the read-only/pure-lookup nature entirely implicit, which is a modest gap.

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 tool takes no parameters, so there is nothing for the description to document; the baseline of 4 applies. The schema is empty and fully consistent with the described no-argument call.

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 ('List') and resource ('cocktail preparation methods'), which disambiguates it from the other list tools like bar_list_glasses and bar_list_ingredients. It doesn't explicitly contrast itself with siblings, but the resource is distinct enough that an agent can tell it apart.

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 guidance on when to reach for this tool versus bar_get_cocktail or bar_list_cocktails, nor any stated preconditions. The usage is only inferable from the name and the word 'List'.

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