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Cisco890

mcp-drink-inventory

by Cisco890

recommend_cocktails_from_inventory

Identify cocktails you can prepare from your current drink inventory. Compare stock volumes for one serving and distinguish missing required versus optional ingredients.

Instructions

Compare stock volumes for one serving; distinguish missing required and optional items.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

The description discloses the core behavior: comparing stock volumes against a one-serving baseline and distinguishing missing required versus optional items. However, there are no annotations to cover safety or side effects, and the description does not mention whether the tool is read-only, what it returns, or how it handles edge cases like insufficient stock for required items.

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?

The description is a single compact sentence with no filler, and it front-loads the main comparison action. It could be slightly clearer by explicitly saying it recommends cocktails, but for a zero-parameter tool it is appropriately 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?

For a tool with no parameters, annotations, or output schema, the description states the essential logic but not the return shape or expected result format. An agent can infer that it returns cocktails with missing-item information, but the lack of any mention of output or follow-up behavior leaves a moderate 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 input schema has zero parameters, so there are no parameter details to explain. With schema description coverage at 100% and no parameters to document, the baseline of 4 is appropriate; the description need not add parameter-level semantics.

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?

The description identifies a specific resource (cocktails from inventory) and a clear distinguishing behavior: comparing stock volumes for one serving and separating missing required from missing optional items. It does not use the verb 'recommend' and the phrasing reads more like an internal computation than a user-facing recommendation action, which keeps it from 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 explicit guidance on when to use this tool versus siblings such as get_cocktail_recipe or get_inventory_summary. The context of 'from inventory' and comparing stock volumes implies the use case, but the description does not state when to prefer this tool or when an alternative would be more appropriate.

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