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

With no annotations, the description carries the full burden and does so richly: accents are preserved via combining marks, some characters stay plain, those are surfaced in notNative and per-part missing flags, and it runs locally with no usage limit. An agent knows the output shape and limitations before calling.

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?

Front-loaded with purpose, followed by caveats, output hints, the classic flag, and invocation guidance. Sentences are dense and occasionally long, but nearly every clause carries information an agent needs; little is wasted.

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?

There is no output schema, so the description compensates by describing the return structure and its edge-case fields (notNative, missing: true). Combined with invocation and character-coverage caveats, nothing needed to call it correctly is missing.

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 baseline is 3, but the description adds real meaning beyond the schema: omitting style means all 22, classic strips accents first (ñ becomes n), and it explains result fields (notNative, missing) the schema never mentions.

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 ('Turns text into Unicode styles'), enumerates the style families, and gives the count (22 styles). It also routes the agent to the sibling list_styles for ids, so it is distinguishable from siblings without opening a schema.

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?

Explains exactly how to invoke: pass one style id, several, or none for all styles, and points at list_styles for valid ids. It gives the condition for classic (fonts that render combining accents badly), but there is no alternative styling tool to compare against, so no explicit when-not-to-use.

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