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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering safety and idempotency. The description adds a meaningful behavioral detail the annotations lack: the site publishes no total, so 'last_page' indicates listing depth. This goes beyond the schema and helps the agent understand pagination and output expectations without contradicting the annotations.

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?

Three sentences, front-loaded with the core action, then necessary context about category sourcing and pagination. Every sentence provides distinct value; no filler or repetition. The length is appropriate for the tool's moderate complexity.

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?

Given the output schema exists, the input schema is fully described, and annotations cover safety and idempotency, the description completes the picture: how to obtain a valid category, that pagination is bounded by a last_page indicator, and that each row links to get_recipe. Nothing essential an agent needs to invoke the tool correctly is 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 100%, so baseline is 3. The description does not introduce semantics beyond the schema for page and limit; it only reinforces the category format already described in the schema ('as a number and a name together'). It adds minor context about 'rows_published' and 'last_page', but these refer to output fields, not parameter meaning. No material enhancement over the schema.

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 opens with a clear verb+resource: 'Read the recipes of one Supertoinette category, page by page.' It specifies the resource as a category and differentiates from siblings by referencing list_categories for the identifier and get_recipe for individual recipe reads. The purpose is unmistakable and distinct from search_recipes.

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 gives practical guidance on sourcing the category ('taken from list_categories or from the 'tags' of a recipe, and never assembled by hand') and implies the pagination workflow via 'last_page'. While it mentions get_recipe as the tool that reads individual rows, it does not explicitly contrast with search_recipes or state when browsing by category is preferred over searching. Still, the context is clear enough for an agent to decide.

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?

Beyond the readOnlyHint and idempotent annotations, the description discloses specific behaviors: missing times return null instead of zero, and rescaling reports whether arithmetic landed exactly or required rounding to measurable amounts. These details add genuine value beyond what annotations convey, with no contradiction.

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 sentences, front-loaded with purpose and identifier format, then packed with behavioral notes. No filler—every sentence and clause contributes actionable information.

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 a detailed output schema present and annotations covering safety, the description adequately covers what an agent needs to call the tool: identifier extraction, handling of missing data, and optional rescaling behavior. No critical gaps remain.

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 100%, so parameters are already well-documented. The description adds extra nuance for 'servings' (rounding behavior, refusal condition) and clarifies id format with a concrete example. This enriches the schema but is not essential, hence slightly above the baseline of 3.

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 'Read one recipe on Supertoinette by its identifier' with a concrete example of the address format. It clearly differentiates from siblings like search or browse by focusing on single-recipe retrieval and enumerates returned fields (ingredients, steps, times, difficulty, cost).

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 description gives clear context: use the id from the URL and optionally pass 'servings' to rescale. It also notes when servings is refused (no scaling number in site wording) and suggests 'Search for a dish when you do not have one' in the parameter schema, acting as an alternative pointer. However, it does not explicitly list exclusions or compare to each sibling, leaving room for slight ambiguity.

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, covering safety. The description adds valuable context beyond annotations: the rating wording scale ('Bon accord' to 'Accord parfait'), the alphabetical ordering of the index, and the mechanism for locating dish identifiers. This goes beyond minimal disclosure.

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 three sentences, each contributing information: purpose, rating scale, and the page/index relationship. It is front-loaded with the primary action and avoids fluff. Slightly long but every sentence is relevant, so it earns a 4.

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 tool has two modes and an output schema, so the description covers the necessary usage context: how to get ids, the index ordering, and the rating scale. It does not explain output format, but the presence of an output schema makes that unnecessary. Missing error-handling details are minor for a read-only tool.

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 coverage is 100%, so both parameters are already documented. The description adds meaning by explaining 'id' as 'the number in a dish's address' and 'page' as reading the index, plus clarifying the mutual exclusivity ('Give this or 'page''). This enriches the schema's baseline.

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 ('Read') and resource ('the wines Supertoinette ranks for one dish'), and clearly distinguishes the tool from siblings like get_recipe or search_recipes by focusing on wine pairings. It also explains the two invocation modes (by dish id or by index page), making the tool's purpose unambiguous.

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 description explains when to use each parameter (id vs. page) and how they relate (the index provides identifiers). It does not explicitly compare this tool to alternatives, but the distinct purpose and sibling names make the selection clear. Since there is no explicit 'when not to use' guidance, it falls short of a 5.

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 mark the tool read-only, idempotent, and non-destructive; the description adds valuable behavior beyond that: entries carry browse_recipes tokens, 'listed_in' reflects site placement, malformed tokens yield pages the site does not hold, and the list is not exhaustive. This is rich, relevant behavioral disclosure with no contradiction.

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 opens with a crisp purpose statement, then each subsequent sentence adds essential information: token usage, placement semantics, the warning against hand-built tokens, and coverage limitations. There is no filler or repetition.

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 an output schema present and annotations covering the safety profile, the description supplies the missing piece: what the entries mean, how to use them with browse_recipes, and how far the categories list extends. An agent has everything needed to invoke and interpret the tool correctly.

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?

The tool has zero parameters, so the baseline is 4 as per the rubric. The input schema is empty and fully described by its 100% coverage, and the description correctly focuses on output semantics rather than inventing parameter guidance.

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 uses a specific verb ('List') and a clear resource ('categories Supertoinette browses its recipes by'), immediately distinguishing it from sibling tools like get_recipe or search_recipes. It also names browse_recipes as the downstream consumer of the returned tokens, further clarifying its role.

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 description gives clear context: use this tool to obtain category tokens for browse_recipes, and warns not to hand-construct tokens. It also notes the tool's coverage limitation—tag-based categories are not included—but it does not explicitly name an alternative tool for those cases, leaving some routing 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?

Beyond the readOnly, idempotent, and non-destructive annotations, the description discloses meaningful behavior: per-line outcome statuses ('scaled', 'rounded', 'unscaled'), the fact that no unit-system conversion happens, and that approximate measures keep their own size. This gives the agent a clear model of what the tool will and will not do.

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 compact and front-loaded: the main action is stated first, followed by essential parameter constraints and behavioral outcomes. Each sentence contributes information that is not already visible in the schema or annotations.

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 pure transformation tool with rich annotations age and an output schema, the description covers the essential contextual pieces: input mode selection, result statuses, unit handling, and offline behavior. Nothing critical is missing for an agent to call it correctly.

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?

The input schema already describes each parameter, so the description does not need to compensate for coverage gaps. It adds real value by explaining the mutual-exclusion relationship between 'factor' and the two servings counts, and clarifies that servings must be supplied together.

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 resource (French ingredient lines) and a precise operation (rescale), plus the offline qualifier, which clearly sets it apart from the retrieval-oriented sibling tools. It does not explicitly name a competing sibling, so it stops short of the strongest possible 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?

It gives solid within-tool usage guidance by requiring either 'factor' or the servings-count pair, and it explains what will happen as a result. However, it provides no explicit guidance on when to choose this tool over the listed sibling tools, leaving tool-selection context implied.

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 substantial behavioral detail beyond the annotations: the absence of 'total_available', the meaning of 'last_page', the behavior of 'facets', the exact spelling requirement for categories, and the dropped-filter behavior for unknown categories. This gives an agent realistic expectations about results and edge cases.

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 compact yet information-dense, opening with the core action and then covering essential edge cases without repetition or filler. Every sentence contributes to correct invocation or result interpretation.

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 read-only search tool with a detailed output schemaaren, the description covers all non-obvious behavior: pagination boundaries, the meaning of null totals, facets, category case sensitivity, and the dropped-filter response. The agent has everything needed to call the tool correctly and interpret results.

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 coverage is 100%, so the baseline is 3. The description restates some of that context, particularly around 'category' and facets, but does not add entirely new parameter semantics beyond what the schema already documents. It is adequate but not an enhancement.

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 action ('Search Supertoinette') with a clear resource ('a dish or an ingredient') and links results to the get_recipe tool, making its purpose unmistakable. It is distinct from browse_recipes because it is explicitly a search by dish or 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 description clearly establishes when to use the tool: when searching by dish or ingredient construction, and explains how to follow up with get_recipe. It does not explicitly name alternative tools or exclusion cases, but the contextual signals from sibling tool names make the intended use clear.

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