deepl_translate_text

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions 'neural translation engine' but omits details like rate limits, character limits, cost implications, response format, or the fact that free tier auth keys end with ':fx' (only mentioned in schema). The agent lacks critical behavioral context.

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?

The description is a single sentence, which is concise but too short to be useful. It front-loads the verb but lacks structure and additional pertinent details. Could be expanded to include key constraints or usage notes.

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 tool has 7 parameters, 3 required, no output schema, and no annotations, the description is insufficient. It does not explain what the return value looks like, authentication requirements, or important limits (e.g., max 50 texts). Completeness is poor.

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 description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema—it simply names the tool's action without commenting on parameters like auth_key, text, or target_lang. No improvement over 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 clearly states the tool's action ('Translate text into another language'), the resource ('DeepL's neural translation engine'), and distinguishes it from sibling tools like deepl_translate_document (which handles documents) and deepl_get_usage/deepl_list_languages (which are about usage and language listing).

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?

The description provides no guidance on when to use this tool versus alternatives, such as deepl_translate_document for document translation, or when to consider the required auth_key or language codes. No when-to-use or when-not-to-use context is given.

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