furigana_name_readings

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

The annotations already indicate read-only and open-world behavior. The description adds meaningful context beyond these by stating the output includes probabilities and that names are ambiguous without context, which explains why the tool returns multiple candidate readings rather than a single result. It does not contradict 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 a single, front-loaded sentence that directly states the action and key qualifiers (probabilities, ambiguity, name types). No unnecessary words 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?

The tool is simple with two parameters, and the schema plus annotations cover most essentials. The description provides a hint about the output structure (list of readings with probabilities), but it does not specify details such as ordering, empty results, or probability format. This is a minor gap, so 4 is appropriate.

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%, with both parameters already explained ('A Japanese name' and 'Hint for the kind of name'). The tool description reinforces the name types and notes ambiguity, which slightly augments the schema, but it does not add significant additional meaning about parameter usage or format. Thus a baseline of 3 is appropriate.

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 uses a specific verb ('List') with a clear resource ('possible readings of a Japanese name'). It explicitly mentions the types (person, company, place) and distinguishes the tool by highlighting the probability output and ambiguity, setting it apart from likely siblings such as furigana_convert or furigana_classify.

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 context for when to use this tool: when a Japanese name is ambiguous and multiple readings are possible with probabilities. It does not explicitly name alternative tools or state when not to use it, but the context is strong enough to guide an agent effectively.

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