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recipe-scaler

Read-onlyIdempotent

Scale a recipe's ingredient quantities to a new serving count. Multiplies parseable amounts by target_servings / original_servings; passes 'to taste', 'pinch', and lines with no quantity through unchanged. Handles fractions, mixed numbers, decimals, and ranges. Does not convert between units — '2 cups' scales to '4 cups', not to grams.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ingredientsYesIngredient list, one per line, free-form. Recognized forms include '2 cups flour', '1 1/2 tsp salt', '0.5 lb butter', '1-2 cups broth'. Lines with no parseable quantity (e.g. 'salt to taste', 'a pinch of pepper') pass through unchanged.
target_servingsYesThe serving count you want the recipe to produce. Must be > 0. Example: cooking for 6 instead of 4 → 6.
original_servingsYesThe serving count the recipe was originally written for. Must be > 0. Example: a recipe that says 'Serves 4' → 4.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ratioYestarget_servings / original_servings.
ingredientsYesOne entry per non-empty input line, in input order.
target_servingsYes
original_servingsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

The description goes well beyond the annotations by detailing the exact scaling formula, handling of unparseable lines, support for fractions/ranges, and the unit limitation. This gives the agent a strong understanding of edge cases and output behavior, complementing the readOnly and idempotent hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences each earn their place: first states the primary purpose, second explains behavior for edge cases, third clarifies a key limitation. No redundancy or filler.

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

Completeness5/5

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

Given the presence of an output schema and fully described parameters, the description covers all necessary behavioral details: formula, pass-through cases, number formats, and unit handling. It is complete for a tool of this complexity.

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?

The input schema already provides 100% coverage with clear descriptions and examples for each parameter. The description reiterates the scaling formula and pass-through behavior, which adds slight context but doesn't significantly improve parameter understanding beyond what the schema offers.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Scale') and resource ('a recipe's ingredient quantities') with a clear outcome ('to a new serving count'). It distinguishes from sibling tools by focusing on recipe-specific scaling rather than generic calculators or converters.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies usage for scaling recipe ingredient quantities and explicitly states what it does not do ('Does not convert between units'). While it doesn't name an alternative tool, it provides sufficient context for when to use this tool and when not to (e.g., for unit conversion).

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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