get_official_links

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds caveats like 'canonical' and 'when available', which hint at authority and conditional availability of docs. However, it does not disclose the return format (e.g., array, JSON), potential rate limits, or whether authentication is required. The description is adequate for a simple read operation but not rich.

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 that front-loads the core action and resource. Every word contributes: 'canonical' explains authority, 'website, support, docs when available' specifies scope without verbosity. There is no fluff or redundancy.

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 simple read-only tool with no parameters and no output schema, the description is mostly complete. It states what it returns (a list of official links) and the object (Nano Banana Pro AI). The lack of an explicit return format is a minor gap, but the term 'list' implies a collection. The description does not mention when to prefer this over siblings, but that's covered under usage guidelines. Overall, it meets the needs of a straightforward 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?

The tool has zero parameters, so schema coverage is effectively 100% (vacuously true). Per the rubric, 0 params gives a baseline of 4. The description adds no parameter information (unnecessary), but it correctly implies the tool needs no inputs. This is appropriate for a parameterless tool.

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: 'Return the canonical list of official links for Nano Banana Pro AI'. It specifies the verb ('Return'), the resource ('official links'), and even qualifies what those links include ('website, support, docs when available'). This distinguishes it from siblings like list_styles and get_pricing, which have entirely 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?

The description implies when to use the tool (when you need official links) but does not explicitly mention alternatives or exclusions. There is no reference to sibling tools like list_styles or get_pricing, so the agent must infer the correct context. This is implied usage rather than explicit guidance.

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