get_legislator

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

With no annotations, the description carries full burden. It discloses return format (JSON string) and error handling (Chinese error messages), but lacks details on data freshness, authentication, or output structure beyond what the output schema provides.

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 extremely concise: a single-line purpose followed by structured Args, Returns, and Raises sections. Every sentence is necessary 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 two-parameter tool with an output schema, the description covers purpose, parameters, return format, and error handling. It lacks only minor contextual details like prerequisites or limitations.

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%, so baseline is 3. The description repeats the same examples as the schema ('term: 11, name: 韓國瑜'), adding no new semantic meaning beyond what's already in the input 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 clearly states '取得特定立法委員的詳細資訊' (get detailed info of a specific legislator), identifies the verb and resource, and includes parameter examples, distinguishing it from sibling tools like list_legislators.

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 implies usage by specifying required parameters (term and name) with examples, but does not explicitly state when to use this tool vs alternatives or any exclusions.

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