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 indicates a read-only operation ('Return') and adds the caveat that docs are included 'when available,' which is useful. However, it does not detail the exact return format or any potential limitations (e.g., if links are missing). The core behavior is transparent enough for a simple 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 a single, well-structured sentence with no wasted words. It conveys the essential information immediately.

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 simplicity (no parameters, no annotations, no output schema), the description provides a sufficient overview of what the tool returns. It could be more explicit about the exact structure of the links, but for typical use cases, the description is adequate.

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 has zero parameters, so the description adds no parameter semantics beyond what the schema shows. Per the rubric, a 0-parameter tool gets a baseline of 4, which is appropriate here.

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 the tool's function with a specific verb ('Return') and resource ('canonical list of official links for Gemini 3 Online'), and even specifies the categories of links (website, support, docs). This clearly distinguishes it from siblings list_models and get_pricing, which have different purposes.

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 explicit when-to-use guidance or mention of alternatives. The intended usage is implied by the tool's name and purpose, but the description does not provide context such as 'Use this when you need official URLs' or 'For pricing, use get_pricing.' Thus it meets the criterion for implied usage but lacks clear guidance.

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 must disclose behavioral traits. It only says 'Return' without explaining whether the result is a URL, object, or other type, nor does it mention authentication, side effects, or other relevant behavior. This is 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 a single, focused sentence with no filler. It front-loads the core action and resource, 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 the simplicity of the tool (no parameters, no annotations, no output schema), the description provides basic purpose but leaves the return format ambiguous. The term 'pricing entry point' could be interpreted in multiple ways, and without an output schema, more detail about the return value would improve completeness.

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 schema is trivially complete and requires no additional explanation. The description does not need to add parameter semantics, and it does not contradict 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 uses a specific verb 'Return' and clearly identifies the resource as 'canonical pricing entry point for Gemini 3 Online.' This is distinct from sibling tools like list_models and get_official_links, making the purpose immediately clear.

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 that the tool is used to retrieve pricing information, but it does not explicitly state when to use it over alternatives. No exclusions or alternative guidance are provided, leaving the usage context inferred rather than stated.

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 must carry the behavioral disclosure burden. It does add context by noting the list is 'canonical' and includes 'capability notes,' which hints at the scope and content. However, it does not explicitly state that the operation is read-only, side-effect-free, or whether authentication is required. For a simple list tool, this is adequate but not highly transparent.

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, concise sentence that front-loads the core action ('Return the canonical list of chat models') and adds a small detail ('with capability notes'). Every word earns its place, with no redundancy 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?

Given the tool's simplicity (no parameters, no output schema), the description provides the essential information: what it returns and that it includes capability notes. It does not specify the exact return structure, but for a list endpoint this is sufficiently complete for an agent 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?

The tool has zero parameters, so the input schema is empty and schema coverage is 100%. Per the rubric, 0 parameters gives a baseline of 4. The description appropriately adds no parameter details because there are none to document.

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 the tool returns 'the canonical list of chat models exposed on the site, with capability notes.' It uses a specific verb ('return') and resource ('canonical list of chat models'), and the mention of 'capability notes' adds specificity. It distinguishes itself from siblings like get_pricing and get_official_links by focusing on models rather than pricing or links.

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 usage when one needs the list of chat models, but it does not explicitly state when to use this tool versus alternatives such as get_pricing or get_official_links. It provides no exclusions or cross-references, so guidance is implied rather than explicit.

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