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nutrition-intelligence

explain

Every fact behind one value: each source, its proof rank and date, which one is published and why. Use before trusting a surprising number.

Input Schema

NameRequiredDescriptionDefault
idYesEntity id, e.g. fd_k3m9x2q8vt7w4p (food), pr_ (product), sp_ (supplement), mi_ (menu item), rc_ (recipe). A source id also works: fdc:<USDA fdcId>, ndb:<NDB number>, dsld:<DSLD id>, fndds:<food code>.
propertyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral burden. It discloses the provenance fields returned and the published-vs-alternative rationale, implying a read-only lookup, but it does not explicitly state read-only behavior, permissions, error handling, or whether any state changes.

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?

Two tightly written sentences front-load what the tool returns and follow with a clear decision rule. The colon-delimited list is efficient, and no wording is redundant or filler.

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?

The tool is simple, but with no annotations and no output schema, the description should supply enough context for correct invocation. It describes the provenance output and one usage cue, yet leaves the property parameter and read-only behavior under-specified, so an agent may understand the purpose but hesitate on exact arguments or safety.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50%: id is well documented in the schema, but property has no schema description. The description only implies that property identifies the value being explained; it does not specify accepted property names, format, or how entity ids and source ids should be chosen.

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?

States a specific outcome: every fact behind one value, including each source, proof rank, date, published choice, and rationale. This makes the provenance/explanation purpose clear, though it does not explicitly differentiate itself from siblings such as get, describe, or verify.

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?

Provides one concrete usage trigger: use before trusting a surprising number. However, it does not state when not to use it, name alternatives for ordinary lookups, or give prerequisites or fallback behavior.

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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