Gluten-free

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

With no annotations, the description carries the transparency burden and does it well: it lists exactly what is included and explicitly states that price and Amazon ratings are unavailable. This prevents false expectations about the returned data. It does not discuss error behavior or rate limits, but those are less critical for a simple read-by-slug tool.

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 efficient and front-loaded: the first clause states exactly what the tool does, the 'Inclut' list adds concrete return fields, and the final sentence flags a limitation. Every sentence earns its place with no repetition or filler.

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 retrieval tool with no output schema, the description is complete: it names the input, enumerates the output fields, states what is not returned, and the schema provides the slug format. An agent has enough context to invoke it correctly and interpret the result.

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 documents the only parameter, slug, at 100% coverage, including an example and a pointer to search_products. The main description adds 'par son slug' but no additional semantic detail beyond the schema. A baseline of 3 is appropriate because the schema does the heavy lifting.

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 ('Récupère') and a precise resource: the complete product sheet by slug. It enumerates the exact fields returned, which clearly distinguishes it from the sibling search/list tools. The retrieval mechanism (by slug) is explicit and actionable.

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 implies when to use the tool: when you have a product slug and need the full product sheet. The parameter schema adds that the full slug list is available via search_products, which provides useful prerequisite guidance. However, the main description gives no explicit when-to-use versus list_comparatifs or direct alternatives.

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?

With no annotations provided, the description carries full disclosure burden. It states the exact contents of each entry (slug, title, URL, product slugs) and the fixed count of 8. It doesn't explicitly state it's read-only, but that is intuitively obvious for a list operation, so it provides sufficient behavioral context without surprises.

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 a single, front-loaded sentence that immediately states the tool's purpose and enumerates the returned data. There is no redundant filler, making it highly concise and well-structured.

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 there is no output schema, the description fully explains what the tool returns: exactly 8 comparatifs, each with slug, title, URL, and product slugs in ranking order. This is sufficient for an agent to invoke and interpret the result correctly without further context.

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 no parameters, and the schema is empty. The description correctly contains no parameter-specific information. Since the baseline for 0 parameters is 4, this is appropriate; there is nothing to add beyond the schema, and the description doesn't need to compensate.

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 ('Liste') and resource ('les 8 comparatifs structurés') and clearly enumerates the exact fields returned for each item, which distinguishes it from sibling tools that focus on products or search.

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 tool is a parameterless list operation, so its purpose itself implies when to use it (to retrieve all comparisons). While it doesn't explicitly mention alternatives, the context of sibling tools (get_product, search_products) makes the distinction clear, but no explicit 'when not to use' guidance is given.

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?

With no annotations, the description carries the full burden of behavioral disclosure. It states what the tool returns (nom, marque, description, liens) and explicitly notes that Amazon prices and ratings are unavailable. It does not discuss side effects, but 'Recherche' plus the return fields strongly imply a read-only search operation.

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 a dense but reasonably sized single paragraph that starts with the core purpose and then adds filter details and return behavior. It could benefit from clearer line breaks or bullets, but every sentence is informative and there is no 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?

Given no output schema and no annotations, the description covers the essential calling context: filter semantics, keyword behavior, and return fields. It does not mention sorting, result wrapping, or when to prefer sibling tools, but an agent has enough to invoke 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?

Schema coverage is 100%, so the baseline is 3. The description adds real value beyond the schema by mapping category values to product types and giving concrete brand and keyword examples, which helps an agent select meaningful filter values.

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 'Recherche dans le catalogue de produits sans gluten', naming the action and resource clearly. It goes on to list filters and returned fields, making it distinct from get_product and list_comparatifs, though it does not explicitly name those siblings.

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 concrete usage context by explaining the category values and how to use the query parameter with suggested keywords like 'pates' and 'pain'. It does not provide explicit exclusions or contrast with sibling tools, but the intended use is clear.

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