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

With no annotations, the description carries full burden. It discloses important behaviors: preserves paragraph structure, handles HTML entities, uses NMT, and supports auto-detection. It does not mention rate limits or auth, but covers key aspects.

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 well-structured with a high-level summary, followed by clear Args and Returns sections. It is concise, with every sentence adding value and no redundancy.

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?

The description is fully complete given the tool's complexity and lack of output schema. It covers all parameters, explains the return format, and provides usage context. No gaps remain.

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?

The description adds significant meaning beyond the sparse input schema. It explains that text may include multiple paragraphs, gives example BCP-47 codes for target, and specifies the default for source ('auto'). This compensates for the 0% schema description coverage.

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 that the tool translates text between languages using neural machine translation, supports 100+ languages, auto-detection, and preserves structure. It also lists specific use cases, distinguishing it from unrelated sibling 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?

The description provides clear when-to-use guidance (document translation, multilingual content, international users) but does not explicitly mention when not to use or suggest alternative tools. However, the sibling tools are all different, so confusion is unlikely.

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