translate_llm_v1_enrich_translate_post

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

With no annotations, the description must disclose operational behavior. It mentions 'using LLM' and 'high-context accuracy' as behavioral traits, and notes the cost per request, but omits essential aspects like synchronous vs. asynchronous operation, response format, failure modes, and whether any side effects occur. The sparse disclosure is inadequate given the absent 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?

The description is two sentences, with the core purpose first and the cost second. It contains zero filler or redundant phrasing, making it highly efficient and front-loaded.

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?

For a simple translation tool with no output schema, the description is minimally adequate but incomplete. It does not specify source language handling (e.g., autodetection), response structure (e.g., whether the translated text is returned directly), or potential rate limits beyond cost. While the two parameters are fully covered, an agent might still have questions about the expected output format and operational constraints.

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 input schema already documents both parameters with descriptions (text: 'The text to translate.', target_lang: 'Target ISO language code'). The description adds no parameter-specific meaning beyond the schema, so it does not elevate the baseline of 3 despite 100% schema 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 it is a 'Universal translator using LLM for high-context accuracy,' identifying the action (translation), the resource (text), and a distinguishing feature (high-context accuracy). This sets it apart from the many enrich_* siblings that handle dates, amounts, names, etc., leaving no ambiguity about its function.

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 states it is a 'Universal translator,' implying it handles all translation needs, but provides no explicit guidance on when to use it vs. alternatives (though no sibling is a translator). It also lacks notes on constraints such as text length limits or when not to use it, leaving usage context implicit rather than explicit.

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