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

Beyond the annotations it discloses billing ($0.01/call via x402 USDC or card key, first 25 free, failed calls free), that repeats are charged (consistent with idempotentHint=false), and the long-text handling that splits at sentence ends and verifies so a cut-off translation is never charged. These are exactly the cost and correctness traits an agent cannot get from structured fields.

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?

It is a single front-loaded paragraph that leads with the operation, then use cases, then cost. The parenthetical model names and pricing clauses make it dense, but each clause carries information an agent would otherwise lack.

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 output schema and three simple parameters, the description covers cost, detection, input limits and long-text handling, which is nearly everything needed to call it correctly. It never states what the response contains (translated text, detected source language), which is the one remaining gap.

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 schema already documents all three parameters; the description mainly restates that the target is an ISO code with a longer example list (en, sv, de, fr, es, zh, ja) and that the source is auto-detected. That adds marginal meaning but no format or validation detail beyond the schema.

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 opens with a specific verb+resource ('Translate text between languages') and names the underlying models and detection behavior, so the agent knows exactly what the call does. It does not differentiate itself from the sibling ai_translate, which leaves ambiguity between two similarly named tools.

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 concrete when-to-use context ('localise messages, documents, product copy and support replies') plus a worked example (text=Payment received, to=sv), which is clear guidance. There are no exclusions or pointers to alternatives such as ai_translate, so routing between the two translation tools is left to inference.

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