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

The description discloses meaningful behavior beyond the annotations: it requires a key with Clinical access, consumes monthly character quota, preserves English terms/numbers/dates exactly, and maps Hebrew drug spellings back to English while preferring known_terms and account terms. These details are valuable and non-contradictory.

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 three concise sentences with no filler. It front-loads the core task, then adds the most important operational details: faithfulness of the conversion, parameter preferences, and access/quota constraints.

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?

Given the output schema exists and the parameter schema is rich, the description completes the picture by covering auth requirements, quota impact, and transformation rules. No critical operational detail needed to invoke the tool 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 description coverage is 100%, and the schema already documents text, glossary, and known_terms individually. The description adds value by explaining the mapping preference and how glossary/known_terms fit into the overall behavior, going slightly beyond the baseline.

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 identifies the verb ('Turn') and the specific resource: a Hebrew clinical question becomes an English query for record search or an English model. This distinguishes it from generic translation siblings by focusing on query generation rather than general text translation.

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?

It gives useful context about when to use it ('for a record search or an English model') and mentions the prerequisite clinical access key and quota. It does not explicitly name alternatives like clinical_translate or translate, so the agent must infer the distinction from the purpose rather than from explicit exclusions.

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