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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds a useful domain constraint about comparability (basis/preparation must match), but says nothing about failure behavior when products are incomparable, rate limits, or scope.

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 the verb and cardinality first and the conditional constraint second — no filler. It is arguably too terse for a two-parameter tool with no schema documentation, which keeps it from a 5.

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?

An output schema exists, so return values need not be explained, and the comparability precondition is stated. But with 0% parameter coverage and two undocumented params, an agent still lacks enough to invoke confidently — the language parameter and barcode input format are unexplained.

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 0%, so the description carries the full burden, yet it only echoes the 2–5 count constraint already encoded in minItems/maxItems. It never states that the input is barcodes (the required array) or what the optional language parameter controls.

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 names a specific verb and resource ("Compare 2–5 products") and scopes the operation with a validity condition. It does not differentiate itself from siblings like get_product or search_products, so an agent must infer when comparison beats a simple lookup.

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?

It supplies a real precondition — only compare when normalized nutrition basis and preparation match — which is genuine usage guidance. However, it never names an alternative or says when not to use this tool versus search_products or get_product, leaving the sibling choice to inference.

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 readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds one genuinely new behavioral note — that nutrition/allergen data is informational — but says nothing about miss behavior for an unknown barcode or about the external-service nature beyond the openWorld hint.

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?

Two tight sentences with the core action and key front-loaded and no filler. Slightly thin rather than padded, but efficient.

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?

An output schema exists, so return values need not be described, and annotations cover safety. What remains missing is the language parameter's effect and the not-found case, which is a modest gap for a simple single-record read.

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 0%, so the description carries the full burden. It hints that barcode is the lookup key but gives no format constraints, and the 'language' parameter is never mentioned anywhere, leaving half the parameters semantically undocumented.

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 ('Read one Open Food Facts product') and the lookup key ('by barcode'), which cleanly separates it from search_products and compare_products. It does not explicitly name those siblings, so it stops short of a 5.

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?

'Read one ... by barcode' implies the usage condition (you already have a barcode), but there is no explicit when-to-use/when-not statement and no routing to search_products for name or category lookups. Usage must be inferred.

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 readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds nothing beyond the verb: no result format, no behavior for unmatched queries, no note on the limit default or language fallback, so it earns little credit even against the lower annotated bar.

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 waste, but it is terse to the point of under-specification for a four-parameter tool. Brevity here reflects omission rather than efficient editing.

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?

An output schema exists, so return values need not be explained, but with 0% schema coverage and no usage guidance the definition is not complete enough to call the tool confidently. Language handling and the meaning of the limit cap are left entirely to inference.

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 0%, so all four parameters (query, taxonomy, language, limit) rely on names alone. The description hints at the query/taxonomy pairing but adds no meaning for language matching rules or limit semantics, leaving the coverage gap uncompensated.

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 (autocomplete) and resource (Open Food Facts taxonomy), which is clear enough to distinguish it from get_product and compare_products. However, it does not clearly separate itself from search_text, which could also be read as a text-autocomplete tool, so it falls short of full sibling differentiation.

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?

There is no guidance on when to use this tool versus search_text or search_products, no mention of prerequisites, and no exclusions. The agent must infer the use case entirely from the one-line purpose.

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 readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds nothing beyond that: no note on pagination behavior, result caps (page_size max 20, page max 1000), or that taxonomy values must be resolved first.

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 short sentence with no padding and a clear front-loaded verb, but the brevity is under-specification rather than efficiency given the 7-parameter surface. It is structurally fine but leaves too much unsaid.

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?

An output schema and annotations exist, so return values and safety need not be described, but for a 7-parameter search with zero schema descriptions and no sibling differentiation the definition is materially incomplete. It omits filter semantics, pagination behavior, and the relationship to get_taxonomy.

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 0% across 7 parameters, so the description carries the full burden, yet it only alludes to 'taxonomy filters' generically. It never maps that phrase to brand/country/category, nor explains the regex/format constraints, page/page_size limits, or the nutriscore enum, leaving most parameters undocumented anywhere.

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 verb and resource are clear ('Search Open Food Facts products'), which is better than a tautology, but 'with documented taxonomy filters' is vague and does not distinguish this tool from the sibling search_text or get_taxonomy. An agent cannot tell from the description which search entry point to pick.

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?

There is no when-to-use guidance, no exclusions, and no mention of the sibling tools (search_text, get_product, compare_products). The phrase 'documented taxonomy filters' hints that filters must come from a taxonomy, but never says to call get_taxonomy first to obtain valid values.

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 readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered elsewhere. The description adds nothing beyond that — no pagination behavior, result caps (page_size max 20), rate limits, or what the search backend actually matches on.

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?

It is a single short, front-loaded clause with zero padding, which is structurally fine. But the brevity here is under-specification rather than discipline — the sentence is too thin for a 4-parameter search tool with siblings to disambiguate.

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?

An output schema exists, so return values need not be described. Still, for a tool with four undocumented parameters, an ambiguous sibling, and no stated scope or limits, the one-clause description leaves essential selection and invocation context missing.

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 0% across all four parameters (query, page, page_size, language), so the description carries the full burden and fails to explain any of them. "Full text" only loosely hints that query is free-text; page, page_size, and language get no mention at all.

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 gives a specific verb+resource ("Full text product search") and names the backing engine, so the basic operation is clear. However, it does nothing to distinguish this from the sibling tool search_products, which sounds like it does the same thing, leaving the agent to guess which one to call.

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?

There is no statement of when to use this tool versus search_products, get_product, or compare_products, and no prerequisites or exclusions. The presence of a near-identical sibling makes the absence of routing guidance a real gap.

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