Gluten-free

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

Annotations are absent, so the description must disclose side effects, but it only states retrieval. No explicit statement about read-only nature or potential errors, though it's implied as a GET-like 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?

Single concise sentence listing included fields; no redundant or promotional content, 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?

Despite no output schema, the description explicitly lists the fields returned (name, brand, category, etc.), making the return content clear and sufficient for the tool's simple purpose.

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 schema fully describes the only parameter 'slug' with an example and a pointer to search_products; the tool description adds no extra parameter information beyond what the schema already provides.

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?

Clearly states it retrieves the complete product sheet by slug and enumerates the fields included, distinguishing it from the sibling tools (search and list).

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?

Implicitly guides usage by mentioning that the slug list is available via search_products, suggesting a search-then-fetch workflow, but does not explicitly state when to prefer this over siblings.

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?

No annotations are provided, so the description carries the burden. It explains the return fields (name, brand, price, ratings, links) and parameter constraints (default limit, max), but it does not explicitly state read-only behavior or other behavioral traits like pagination or rate limits. The read-only nature is implied but not stated.

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 paragraph but packs a lot of useful info without fluff. It front-loads the main purpose and then details filters and return fields. No unnecessary sentences, though it could be slightly more structured with bullets, but it's acceptable.

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 fully explains what the tool returns (nom, marque, prix, notes, liens). It also details all parameter values and usage examples. For a search tool with 4 optional params, this is complete and self-sufficient.

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 adds significant value by explaining exact category values (e.g., 'epicerie' = pâtes/farines/sauces) and suggesting keyword usage ('pates', 'pain', etc.). This goes beyond the schema definitions.

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 clearly states it searches the verified gluten-free Amazon product catalog, and then details multiple filters (category, brand, keywords) and return fields. This distinguishes it from sibling tools like get_product (specific product retrieval) and list_comparatifs (comparisons).

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 implies usage for search scenarios and provides specific filter values and keyword examples, making it clear when to use. However, it does not explicitly mention when not to use it or direct to siblings, so it lacks explicit exclusions.

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