Foodbe

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

Annotations already establish this is non-destructive and closed-world, but oddly set readOnlyHint=false for what is plainly a lookup, so the description carries some burden. The field enumeration (nutrition, allergens, diets, price, environmental impact) usefully signals the payload's breadth, but there is no output schema to confirm shape, units, or currency, and no failure behavior is described.

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

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

A single front-loaded sentence with no filler, and the field list is a compact way to convey return content. Slightly list-like rather than explanatory, but nothing is wasted.

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

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

With no output schema, the description does the minimum of naming the returned sections, which is the right move. It stops short of the details an agent would want for a one-parameter lookup with no documented response shape: unit/currency conventions, whether missing data returns partial results, or error behavior for unknown ingredients.

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

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

Only one parameter with 100% schema description coverage including an example, so the schema does the work. The description adds nothing about name matching, synonyms, or aliases beyond what the schema states.

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

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

Specific verb ('Get a structured profile') plus a specific resource ('a specific ingredient'), followed by an enumeration of what the profile contains. It implicitly contrasts with the sibling query tools by being a single-ingredient lookup rather than a search, but never names them.

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

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

Usage is only implied: 'a specific ingredient' suggests this is for known-name lookups versus foodbe_query/foodbe_query_all, but the description never says when to prefer this over those siblings or what happens if the name is unknown.

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

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

The description adds useful behavioral context beyond the annotations: it promises a grounded, cited answer and states that the tool refuses rather than guessing when no verified answer exists. However, it does not explain why readOnlyHint is false for a query-style tool, nor does it disclose any state or side effects.

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

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

The description is two tight sentences with the core purpose front-loaded and no wasted text. The refusal behavior is a useful second sentence rather than padding.

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

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

The description covers the primary question and answer behavior, including citations and refusal semantics, and there is no output schema so return-value explanation is limited. But it omits the purpose of 'currentGroceryItems' and does not reconcile the readOnlyHint=false annotation with the query-style operation.

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

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

Schema description coverage is 50%: the required 'question' parameter is documented, but 'currentGroceryItems' has no schema description and is not mentioned in the tool description. The description adds no meaning for that second parameter, leaving the agent unable to infer its role.

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

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

The description states a specific verb and resource: ask a single food question and receive a grounded, cited answer from a fact-checked corpus. It implies a single-question scope that distinguishes it from a likely bulk sibling like foodbe_query_all, but it does not explicitly differentiate from foodbe_ingredient.

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

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

The phrase 'single food question' implies when to use this rather than foodbe_query_all, but the guidance is not explicit. There is no direct mention of foodbe_ingredient, and no when-not-to-use or alternative-routing guidance is provided.

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

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

Annotations already declare destructiveHint=false and openWorldHint=false, so safety is covered. The description usefully discloses the fan-out behavior and the identity of the three responders, which implies higher cost/latency than a single query. It does not disclose return format, whether answers are independent or synthesized, or any limits on question length.

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

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

A single sentence that front-loads the action and immediately enumerates the three voices. No filler, no restatement of the name, and the persona list earns its place by telling the agent what coverage to expect.

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

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

For a one-parameter, no-output-schema tool with annotations present, the description covers what it does and what comes back (three expert answers). The main residual gap is how to choose between this and the sibling foodbe_query, plus the shape of the combined response.

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

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

Only one parameter and schema coverage is 0%, so the description must carry the burden. 'Ask a food question' does establish that the input is natural-language and food-domain, which is real semantic value beyond the bare 'question: string'. However it says nothing about phrasing, length, or whether follow-ups/context are supported.

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

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

States a specific verb and resource ('ask a food question', 'get answers') and scopes it precisely to fan-out across three named expert personas (Neuro, Oracle, Chefy). An agent can tell this is the all-voices variant rather than a single-voice query, though it never names the sibling foodbe_query explicitly.

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

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

The phrase 'all three ... at once' implies this is for when you want broad multi-perspective coverage, which hints at the alternative of querying one voice. But there is no explicit when-to-use/when-not rule, no mention of foodbe_query or foodbe_ingredient as the cheaper single-perspective option, and no guidance on question phrasing.

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