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

Annotations cover the safety profile (readOnlyHint=false, openWorldHint=true, non-idempotent, non-destructive). The description adds genuinely new behavioral context beyond them: the per-call cost ($0.002 USDC on Base) and the x402 payment mechanism, which matters for invoking it.

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 sentences, front-loaded with the core action, then parameter guidance, then usage and cost. No filler, though the language-code list is somewhat verbose.

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?

No output schema exists, but the description sufficiently covers inputs, usage, model, and cost. Return format is unstated, which is a minor gap for a translate tool but not critical.

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 the baseline is 3. The description goes slightly beyond it by expanding the ISO-code examples (en, sv, de, fr, es, zh, ja) and restating that source is optional with default en, adding marginal clarity.

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) and resource (text) plus the exact model (Meta's M2M100 1.2B), which clearly distinguishes it from the many other ai_* siblings like ai_rewrite or ai_summarize-text.

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 an explicit use case ('Use to localise messages and documents'), which helps an agent pick it over generic ai_chat. It stops short of naming when-not-to-use or an alternative tool, so it doesn't reach 5.

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