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nutrition-intelligence

flag

Report a value that looks wrong, or a label photo that looks fake. Free. Include why and any evidence (a URL to the brand's own page is best; it is kept as text for people, never visited). Flags open review tasks. With proof_id (a photo proof, from a card's sources, e.g. "p123" is 123), the flag lands on every value that photo currently proves.

Input Schema

NameRequiredDescriptionDefault
idNoEntity 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>.
reasonYes
proof_idNoA photo proof to flag as fake or wrong: every value it currently proves is flagged.
propertyNo
evidence_urlNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

No annotations exist, so the description carries the full load, and it does disclose non-obvious behavior: the call is free, evidence URLs are stored as text for humans and never visited, and flags open review tasks. It leaves out duplication behavior, the response shape, and whether the reporter's identity is recorded.

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?

Front-loaded with the action and target, then parenthetical clarifications that each add a fact. Three sentences, no filler. It is slightly telegraphic in places ('Free.'), but the density is justified.

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 five-parameter, no-annotation, no-output-schema mutation tool, the description covers behavior and two parameters well. It falls short on the id parameter (which accepts entity IDs and source IDs like fdc:/ndb:) and on property, and it never says what a successful flag returns, such as a review task identifier.

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 40%, so the description needs to compensate, and it does for two of five params: evidence_url ('kept as text for people, never visited') and proof_id (the cascade behavior plus the 'p123 is 123' notation). The id and property parameters get no explanation at all, leaving a real gap.

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 opens with a concrete verb and two resource types: 'Report a value that looks wrong, or a label photo that looks fake.' An agent can tell this is a moderation/reporting tool rather than a read or edit tool. It does not explicitly contrast itself with siblings like feedback or suggest_domain, which keeps it from 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 Guidelines4/5

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

It states the trigger condition (a value looks wrong or a photo looks fake) and tells the caller what to supply ('Include why and any evidence'). It also gives a conditional rule for proof_id: with it, the flag lands on every value the photo proves. It does not say when to prefer a sibling tool such as feedback or suggest_domain.

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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