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

With no annotations, the description carries the full behavioral burden. It does add real value by disclosing the pricing model ('0.005 USDC per call via x402'), which the schema does not state — though the mechanics live in the paymentProof field description. It omits other behavior: rate limits, what happens on unsupported languages, or the shape of the translated result.

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 short sentences, zero filler, and the core capability is front-loaded ahead of the optional-source note and the price. Every sentence contributes a distinct fact.

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 four-parameter, fully documented schema with no output schema, this covers capability, optionality, and cost. The only meaningful gap is that it never says the return is the translated text (and in what form), which is predictable but unstated.

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 100%, so all four parameters, including the x402 payment flow, are already fully documented. The description only reiterates that the source language is optional, adding no syntax, format, or default detail beyond the schema — baseline 3 applies.

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 ('Machine translation between about 100 languages') and names the underlying model (m2m100), which clearly separates it from sibling AI tools like ai_rewrite or ai_summarize. It lacks an explicit 'not for X' clause but the operation is unmistakable.

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?

Usage is only implied: the description mentions source language is optional, hinting at auto-detection, and the cost line hints at the payment flow. There is no explicit when-to-use/when-not guidance or comparison to the many other ai_* siblings, which an agent must infer.

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