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

The annotations already mark the operation as read-only and non-destructive. The description adds valuable behavior beyond that: per-character quota consumption, the account-configurable 10,000-character per-call limit, and the dedicated Kurdish engine. No contradiction with annotations.

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, each earning its place: scope, Kurdish special-case, auto-detection, quota, and size limit. The most important action ('Translate text') is front-loaded, and there is no filler or repetition of the schema.

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?

Given the output schema exists and the input schema documents all parameters, the description covers the operational context an agent needs: quota impact, call-size limits, auto-detection behavior, and where to find the full language list. Nothing critical is missing.

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 adds meaningful parameter guidance by explaining source-language auto-detection and giving concrete target-language examples (ku, ckb, zza, en, de, tr, ar), which helps an agent pick valid values.

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 and resource: 'Translate text between 250+ languages with mazdek AI.' It also highlights the dedicated Kurdish engine and language codes, which makes the tool's scope clear and separates it from siblings like transliterate_sorani.

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 actionable usage context: omit source_language or pass 'auto' for auto-detection, and split texts exceeding the 10,000-character limit. It does not explicitly say when to prefer an alternative sibling, but the target-language list reference points to the relevant companion tool.

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