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nutrition-intelligence

compare

Items side by side on one basis: per_100g, per_serving or per_100kcal.

Input Schema

NameRequiredDescriptionDefault
idsYes
basisNoper_100g
fieldsNoOnly return these nutrient keys (e.g. ["energy","protein"]). Saves tokens. A group name returns every key under it, each as its own value in its own unit, never added or converted: "vitamin_a" gives vitamin_a.rae (µg) and vitamin_a.iu (IU); "carbohydrate" gives carbohydrate.total (includes fibre), carbohydrate.available (excludes it) and carbohydrate.available_mse. A key that is itself a registry key (e.g. "fat") is just that key. A name that matches nothing comes back missing with the closest keys.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.5/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden and supplies almost none of it. It does not state that the operation is a read, how missing nutrients or items with no serving-size data are represented, whether fewer than 2 valid ids errors out, or what the response shape is (no output schema exists).

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

Conciseness3/5

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

One short, front-loaded sentence with no filler, which is structurally clean. However, the brevity crosses into under-specification rather than earning its place: the single clause leaves out the resource being compared.

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

Completeness2/5

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

For a batch tool accepting 2-20 heterogeneous entity ids plus source-id forms, with an enum basis and no annotations or output schema, the description is far too thin. An agent cannot predict return structure, error behavior, or how mismatched entity types are handled.

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 coverage is only 33%, and the two documented parameters (ids, fields) already carry rich inline descriptions, so the description compensates only for 'basis'. Its mention of the three basis values merely restates the enum, and it never resolves the real ambiguity — what 'per_serving' means for an item lacking serving-size data.

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

Purpose3/5

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

The verb 'compare' is clear and the description names the comparison basis (per_100g, per_serving, per_100kcal), which implies a nutrition comparison over the ids in the schema. But it never says what is being compared (nutrients of foods/products) or what the output looks like, and it does not distinguish itself from siblings such as nutrition, describe, or reference_values.

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 at all: nothing says whether to pick this over 'nutrition' or 'describe', whether all ids must be the same entity type, or what happens when a basis is unavailable for an item. The only implied usage is 'give me 2-20 ids'.

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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