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

Annotations indicate idempotentHint=true, and the description aligns by showing deterministic behavior. Beyond that, it adds a specific behavioral detail: 'removes accents', which is not in the schema, and the cost note (1 credit per call) is a unique behavioral disclosure not in annotations.

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 concise, with the core purpose in the first sentence, an illustrative example, and a separate cost note. Every sentence earns its place; it is front-loaded and efficient.

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 pure transformation tool with 2 parameters and no output schema, the description covers the transformation rules, example, and cost. It lacks explicit mention of edge cases (e.g., empty text) but this is a minor gap given the clarity.

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 schema already documents both parameters. The description adds an example for `text` and mentions the separator in the transformation rule, but it doesn't add critical meaning beyond the schema. Baselines at 3 are 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 clearly states the verb 'turns' and the resource ('text' into a URL slug), with a concrete example that demonstrates the transformation. It distinguishes itself from siblings by focusing on slug generation, which none of the sibling tools do.

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 it (when you need a URL-friendly slug) but does not explicitly state when not to use it or provide alternatives. Given the clear purpose, an agent can infer usage, but explicit guidance is lacking.

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