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

Annotations already cover the safety profile (readOnlyHint, openWorldHint), and the description adds real operational context beyond them: per-size pricing, a concrete per-call x402 cost, the batch ceiling, and the default source language. It does not mention error behavior or output ordering for batches.

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?

Three tight sentences with purpose front-loaded, then parameters, then cost. The pricing sentence is dense but earns its place for an x402-priced tool; no filler.

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 4-param tool with no output schema, the description covers purpose, required/optional params, and cost, but omits return shape for batch calls (ordering, mapping to inputs) and the distinction from translate_indic. Adequate but with clear gaps.

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 75%, so most parameters are already documented. The description restates the batch limit and default source_lang (both present in schema) and usefully implies text/texts mutual exclusivity, but adds little new semantic detail. Baseline 3 fits.

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 (Translate), resource (text), scope (~100 languages, M2M-100 model), and batch size. It does not distinguish itself from the sibling translate_indic, so an agent must guess which translation tool applies to Indic languages.

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?

Gives calling context (target_lang required, source_lang optional default en, one text or batch of 20) but no when-to-use/when-not guidance and never names the alternative translate_indic. Usage is implied rather than routed.

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