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

With no annotations, the description must carry the behavioral burden. It usefully discloses that the operation is pure CPU and instant, preserves case, and returns plain ASCII. However, it does not state what happens to non-Latin text, emoji, punctuation, or ambiguous non-ASCII characters, which are important edge cases for a text-normalization tool.

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 two compact sentences, front-loaded with the core operation and immediately followed by the return behavior and performance characteristic. Every sentence contributes useful information, and there is no unnecessary wording.

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 one-parameter text transform with no output schema and no annotations, the description covers the essential purpose, return format, case behavior, and performance profile. It is nearly complete, though it could mention how non-diacritic non-ASCII characters are handled.

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?

There is one required parameter, and schema description coverage is 100%, so the schema already defines the input. The description adds the important semantic detail that case is preserved and output is ASCII, but it does not add parameter-level usage or format details beyond that. The baseline of 3 is 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 gives a specific verb and resource: strip diacritics and accents from text. It also states the output behavior (plain ASCII, no case change), which helps distinguish it from generic case conversion. It does not explicitly name or differentiate against close siblings such as slugify, so it stops short of a 5.

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 explains what the tool does but gives no explicit guidance on when to choose it over alternatives like slugify, case_convert, or ascii_table. It also provides no exclusions or prerequisites. The use case is inferable, but the guidance is not stated.

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