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

With no annotations, the description carries the full burden. It discloses caching behavior (local TM cache first, auto-populates), engine fallback (Groq preferred, then OpenAI), and default source detection. Returns structure is also explained.

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 paragraph of five sentences, well-structured with main action first. It is concise but could be slightly more compact without losing key details.

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 no output schema, the description explicitly lists return fields (ok, translation, fromCache, sourceLang, targetLang, engine). It covers caching, engine fallback, and default behavior, making it sufficiently complete for a translation tool.

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?

Although schema coverage is 100%, the description adds value by explaining the caching logic, default behavior for sourceLang, and the return structure. This context helps the agent understand parameter usage beyond schema descriptions.

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 primary action 'Translate text to a target language' and details the caching mechanism, distinguishing it from a simple translation. However, it does not explicitly differentiate from the sibling 'quick_translate' tool.

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 explains the caching behavior and engine fallback, implying when to use. It notes that sourceLang defaults to 'auto' and only concrete source-lang calls hit the translation memory. However, it lacks explicit when-not or comparison with alternatives.

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