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

With no annotations, the description carries the burden, and it does disclose the qualification rule (lowercase alphanumeric words joined by single hyphens), which is real behavioral content. It does not state the return shape (a boolean) or edge-case handling such as empty strings or leading/trailing hyphens.

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?

Two short clauses, front-loaded with the purpose followed by the definition. The trailing 'Provide value' sentence is minor filler but does not bloat the definition.

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 trivial one-parameter predicate with no annotations or output schema, the essential context (what counts as a slug) is supplied. Only the return value convention is unspecified, which is a small gap for a boolean check.

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%, so the single parameter is already documented, and 'Provide value' restates the schema rather than adding syntax, length limits, or examples. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb and resource ('Check whether a string is a URL slug') and even defines the slug syntax, so an agent can tell it apart from generic validators. It does not, however, explicitly differentiate itself from near-siblings like x402-is-kebab-case or x402-is-url.

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 predicate framing implies usage (call it to test a candidate slug), but there is no explicit when-to-use guidance, no pointer to alternatives such as x402-slug (which generates rather than validates), and no statement of what the result means.

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