dictionary_translate

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, and it does so well. It reveals that results are grouped by source sense, that senses are never silently crossed, that max_senses and limit operate independently, and that count and candidate_count report distinct nested result counts.

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 compact and front-loaded: purpose first, usage guidance second, then parameter semantics. Every sentence adds information that is not obvious from the schema, with no filler or repetition.

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 7-parameter tool with no annotations and an output schema, the description covers the non-obvious behavior thoroughly: sense preservation, result grouping, budget semantics, and count meanings. The only omitted items, such as exact output shape, are already handled by the output schema, so 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 71%, so the description does not need to re-explain every parameter. It adds meaningful semantics for the most confusing parameters: max_senses bounds inspected senses independently, limit is the shared translation-candidate budget, and sense_id comes from a prior dictionary_lookup call. This goes beyond the bare 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 opens with a specific verb and resource: 'Translate a word while preserving its source-sense association.' This clearly differentiates it from sibling lookup, synonym, relation, and rhyme tools, and it names dictionary_lookup as the complementary tool for ambiguous words.

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 explicitly instructs the agent to 'Use dictionary_lookup first for ambiguous words, then pass its sense_id,' giving a concrete when-to-use alternative. It also explains how limit and max_senses should be set relative to one another, which guides parameter choices.

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