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

No annotations provided, so description carries the full burden. It explicitly discloses the pre-launch behavior: 'Before launch, returns the launch date and early-access contact instead of a URL.' This is a key behavioral trait beyond the schema. It doesn't mention other side effects, but for a read-only getter this is adequate.

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: a single sentence for purpose, a sentence for pre-launch behavior, and two parameter explanations. It front-loads the core purpose and adds only necessary details with no waste.

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 is simple with two parameters. The description covers the special pre-launch case, explains parameter sources, and the output schema exists to define return values. The description is complete 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?

Schema description coverage is 0%, so the description must compensate. It fully explains both parameters: 'slug: A product slug from list_products, e.g. "film-shoot"' and 'tier_name: A tier name from that product's pricing_tiers, e.g. "Per-shoot"' – providing source, meaning, and examples for each.

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?

Description states 'Get the checkout URL for one pricing tier of one product' – a specific verb (get), resource (checkout URL), and scope (one pricing tier of one product). It also differentiates from sibling tools by focusing on checkout URL, clearly distinct from list_products (listing) and get_product (product details).

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?

Provides clear context by referencing that slug comes from list_products and tier_name from that product's pricing_tiers, implying the need to call list_products first. It doesn't explicitly state when not to use it or name alternatives, but the context is sufficient for correct usage.

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 full burden. It discloses the breadth of returned information, including dynamic behavior like 'checkout URL once on sale.' It doesn't explicitly state read-only behavior, but 'Get' plus the non-mutating content list makes that implicit, and the output schema covers return structure.

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 front-loaded with the main purpose and effectively organized into a content list followed by an Args section. The list is long but every item adds information an agent would want; 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?

For a one-parameter read tool with an output schema, the description is nearly complete: it names the required input, its source, an example, and the returned content. The only minor gap is not explicitly routing the agent to get_checkout_url when only a checkout link is needed.

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 0%, so the description must compensate, and it does. It explains that slug is 'A product slug from list_products' and gives a concrete example ('film-shoot'), adding meaning the schema's bare 'Slug' title does not provide.

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 ('Get') and a specific resource ('full details for one product'), then enumerates exactly what details are included. This clearly distinguishes it from list_products (which lists products) and get_checkout_url (which is checkout-specific), even without opening the schema.

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 tells the agent to get the slug from list_products, which establishes a prerequisite and workflow context. It does not explicitly name get_checkout_url as an alternative, but the scope is clear enough that an agent would not confuse it with the 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 the burden of behavioral context. It discloses that the tool returns a summarized view (slug, display name, publisher, one-line summary, availability) rather than full product data, and it implies a read-only operation through the verb 'List.' It does not mention pagination or rate limits, but for a parameterless list tool this is adequate.

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, stating the tool's purpose in the first sentence and adding only the necessary output detail and guidance in the second. Every sentence earns its place, with no redundant filler or repetition of schema content.

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 tool's low complexity (no parameters) and the presence of an output schema, the description covers everything an agent needs: what the tool returns, how that output is meant to be used, and where to go for full details (get_product). There are no material gaps for a list endpoint of this kind.

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 takes zero parameters, and the input schema is an empty object. Per the rubrics, a zero-parameter tool receives a baseline of 4; the description has no parameter semantics to add, so this score reflects that the absence of parameters is clear and complete.

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 specific verb+resource statement: 'List every Sklarstad LLC product.' It goes on to enumerate the returned fields, which makes the tool's scope precise and immediately distinguishable from the sibling get_product tool that provides 'full details.'

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 explicitly tells the agent when to use this tool: before calling get_product, to decide which product is relevant. This is a clear usage directive with an explicit alternative, leaving no room for confusion about its role in a workflow.

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