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Charcuterie board calculator

charcuterie_board_calculator
Read-onlyIdempotent

How much cheese, cured meat, crackers, fruit, nuts and jars to buy for a charcuterie board, and what size board, for a guest count.

Input Schema

NameRequiredDescriptionDefault
guestsYesNumber of guests
occasionYesappetizer = before a meal; meal = the board is dinner; cheese-course = after dinner
vegetariansNoGuests who eat no meat

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful scope information by enumerating the outputs produced, but says nothing about how results are expressed (units, rounding, per-item breakdown) — appropriate for a 3 given the annotation coverage.

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 no filler, and the output list is placed after the trigger (guest count) where it belongs. It is dense but readable; a slightly crisper split of what-in vs what-out would earn a 5.

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?

With no output schema, the description does the necessary work of enumerating what is returned: item quantities and a board size. That is nearly complete for a small 3-parameter read-only calculator, though units and whether quantities are totals vs per-guest remain unstated.

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 description coverage is 100%, and the schema even explains the occasion enum values and the guests/vegetarians bounds. The description adds no parameter-level meaning beyond that, so the baseline 3 applies. The mention of 'jars' and specific food categories hints at output content rather than input 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 names a concrete calculation input (guest count) and concrete outputs (quantities of cheese, cured meat, crackers, fruit, nuts, jars, plus board size), which is far more specific than the tool name alone. It does not explicitly distinguish itself from adjacent calculators like party_food_calculator or ham_calculator, 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, no exclusions, and no mention of the sibling calculators that could plausibly be chosen instead (party_food_calculator, ham_calculator, prime_rib_calculator). The agent must infer from the noun 'charcuterie board' that this is the right tool.

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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