ai_slugify

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

With no annotations, the description carries the behavioral burden, and it does disclose the key output traits (ASCII-only, hyphen-separated) that go beyond the tool name. It does not say how non-ASCII characters, casing, or punctuation are handled, nor whether stripping can yield an empty slug.

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 that states the action and the output format with no filler. Every clause earns its place.

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 utility with an output schema present, the description covers what the tool produces and the slug's format. The only meaningful gap is edge-case behavior on unicode/empty results.

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%, so the only source of parameter meaning is the word 'text' in the description, which merely echoes the parameter name. The single parameter is self-explanatory, so this is adequate but adds no real semantics beyond the schema.

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 gives a specific verb ('Convert') and resource ('text'), plus the output form ('URL-friendly slug, ASCII, hyphen-separated'). It is unmistakable against siblings like ai_text_stats or ai_keywords, though it doesn't explicitly name a differentiator.

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?

There is no explicit when-to-use or when-not-to-use guidance, but for a single-purpose transformation utility the applicability is strongly implied by the phrase 'URL-friendly slug'. No alternatives or exclusion conditions are stated.

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