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

Annotations are sparse, but the description adds valuable behavior beyond them: it scrapes a remote URL, runs AI generation, and consumes AI quota. This cost/side-effect disclosure is meaningful even though readOnlyHint is false. It doesn't mention error behavior or rate limits, but the core behavioral traits are covered.

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 two efficient sentences: the first states the core action and result, the second adds workflow context and a resource-consumption warning. Every sentence earns its place with no 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?

With one required parameter, an output schema, and annotations present, the description covers the essential behavior, the workflow context, and the notable side effect (AI quota consumption). Nothing critical is missing for an agent to select and invoke this tool 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% and the single url parameter is already described as 'Website URL to analyze.' The description adds no new parameter-level detail about format, protocol, or constraints, so the baseline score of 3 is appropriate.

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 action ('Scrape a URL') and the produced result ('generate an AI description of the business'), clearly distinguishing it from website CRUD siblings like get_website, create_website, and update_website.

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 gives clear context: it is useful to preview or seed the description before creating a website. It doesn't explicitly list when not to use it or name alternatives, but the intended workflow is evident from the surrounding sibling tools.

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