Skip to main content
Glama
Vegetable Yield Percentage MCP

Vegetable Yield Percentage MCP

Calculate edible weight

calculate_edible_weight
Read-onlyIdempotent

Calculate edible weight and trim waste from a purchased raw vegetable or fruit weight using USDA yield percentages.

Instructions

Edible weight and trim waste from a purchased (as purchased, untrimmed) weight of a raw vegetable or fruit, using the USDA edible yield percent.

Input Schema

NameRequiredDescriptionDefault
foodYesRaw vegetable or fruit in plain words, for example "onion", "red bell pepper", "pineapple", "butternut squash", "broccoli", "avocado".
unitNog, kg, oz or lb. Default g.
purchased_weightYesWeight as bought, for example 5.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior3/5

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

The annotations already establish the safety profile (readOnlyHint, idempotentHint, destructiveHint=false, openWorldHint=false), so the description's main contribution is disclosing the data source (USDA edible yield percent) and the as-purchased starting point. It stays silent on failure behavior for unrecognized foods and on precision/rounding of the returned weights.

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?

It is one compact sentence with the key qualifier ('as purchased, untrimmed') front-loaded and no filler. The sentence is a fragment without an explicit verb, which is a minor readability flaw, but nothing is wasted.

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 simple three-parameter, read-only calculation, the description covers inputs and the two outputs adequately, and there is no output schema to defer to. It is still missing edge-case behavior (unknown food, mismatched unit assumptions) that an agent would want before calling.

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%, so the schema covers all three parameters, including unit defaults and examples. The description adds only a modest gloss: that purchased_weight means untrimmed as-bought weight and that food maps to a USDA yield value. That is the baseline for a fully documented schema.

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 the two outputs (edible weight and trim waste) and the required input (as-purchased untrimmed weight) plus the method (USDA edible yield percent), so the operation is unmistakable. It does not, however, distinguish itself from the siblings calculate_amount_to_buy, get_vegetable_yield, or list_vegetable_yields, which is the difference between a 4 and 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 Guidelines3/5

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

Usage is only implied: the phrase 'from a purchased (as purchased, untrimmed) weight' signals that this is the forward direction, as opposed to calculate_amount_to_buy. There is no explicit statement of when to choose this tool over its siblings, and no note about what it does when the food name is unknown.

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