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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description still adds real context beyond that: "pure computation" confirms no network/side effects and "free" discloses cost, which is not encoded in the 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?

Two short sentences, the purpose front-loaded and the cost/behavior note second. Every clause carries information; nothing is padded.

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 one-parameter, no-output-schema utility the definition is minimally sufficient: the agent knows the input is text and the result is a slug. It omits the transformation rules and any example output, which for a slugifier are the details most likely to surprise a caller.

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 0% for the single `text` parameter, so the description carries the burden of explaining it and does not. It says nothing about slugification rules an agent would need to predict output — lowercasing, diacritic stripping, separator choice, or max length.

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?

"Turn a text into a URL-safe slug" gives a specific verb (turn into) and a specific output artifact (URL-safe slug), which an agent can distinguish from neighbors like bursia_url_encode (percent-encoding) or bursia_case_convert. It stops short of naming those siblings explicitly, so differentiation is inferential rather than stated.

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?

"Pure computation, free" implies the tool is safe to call at will and needs no credentials, which is a light usage signal. There is no explicit when-to-use guidance and no mention of when an alternative (e.g., url_encode, case_convert) would be the better pick.

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