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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior. The description adds meaningful context beyond annotations: it is free, deterministic with no AI inside, nothing is logged, and the response includes confidence, estimated items, sources, version, and warnings.

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 dense but front-loaded, starting with what is detected before moving to response and behavioral notes. Some response-field listing may be redundant with the output schema, but the overall wording is 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 single-parameter detection tool with an output schema and rich annotations, the definition is largely complete: it describes outputs, determinism, privacy, and response metadata. The main gaps are input expectations and explicit routing versus sibling tools.

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?

The only parameter is `text`, but its schema description is empty and the tool description only says the analysis is of 'a text.' It does not add constraints, format expectations, or examples, so it fails to compensate for 0% schema description coverage.

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 resource analyzed and enumerates specific outputs: script proportions, dominant script, RTL/LTR direction, mixed-script flag, digit systems, and script hints. It does not explicitly contrast with sibling tools such as transliterate or convert_digits, so sibling differentiation is left implicit.

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 does not say when to use this tool versus alternatives like transliterate, convert_digits, or normalize_arabic. The output list implies it is for script analysis, but no explicit usage context, exclusions, or alternatives are provided.

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