generate_lorem_ipsum_structured

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

With no annotations, the description carries the disclosure burden. It discloses that generation is token-controlled and costs a fixed micropayment on Base L2, but it does not clarify whether paymentSignature is mandatory, how token control works, or what behavioral guarantees the tool offers.

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?

A single front-loaded sentence conveys the core behavior and content types, with the cost parenthetical at the end. Every phrase earns its place and there is no redundant 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?

The description omits the payload format needed to request specific content types, does not describe the return/output shape, and only hints at payment via a price tag without explaining the settlement workflow. An agent would likely need additional documentation to call 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 description coverage is 100%, so the baseline is 3. The description adds useful context about the kinds of text produced, but the payload parameter remains an opaque JSON string and the description does not explain which keys produce paragraphs versus titles versus emails.

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 names a specific action ('Generates') and resource ('semantic dummy text') and enumerates concrete content types: paragraphs, titles, list items, emails. This clearly distinguishes it from sibling utilities like generate_placeholder_svg, which target visual placeholders rather than structured text.

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 gives an explicit intended context ('for UI mocking'), so an agent can infer when to select this tool. However, it does not name alternatives or state when not to use it, stopping short of full when/when-not guidance.

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