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

No annotations are provided, so the description carries the full disclosure burden, yet it only restates the engine choice already documented in the schema enum ("google" free vs "ai" BYOK). It says nothing about rate limits, auth/BYOK setup requirements, defaults applied, or failure behavior for a tool that depends on external providers.

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 with the action first and the qualifier (engine/provider) after. No filler or redundancy.

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?

With no annotations and no output schema, the description should carry more weight than it does. The schema covers the parameters well, but the description is silent on what is returned and on the BYOK configuration dependency implied by "the configured AI provider".

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%, so the schema already documents text, engine, source_lang, and target_lang with defaults and examples. The description confirms the single-text scope but adds no format, language-code, or engine-selection detail beyond the schema, making the baseline 3 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?

States a specific verb+resource ("Translate one piece of text") and names the backends used, scoping it to a single item which implicitly sets it apart from the translate_batch sibling. It stops short of explicitly naming that sibling, so the differentiation must be inferred from the word "one".

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 phrase "one piece of text" implies the single-item case versus a batch, but no explicit when-to-use, when-not-to-use, or alternative routing (e.g., translate_batch or list_engines) is stated. Usage is only implied.

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