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

With no annotations, the description carries the full behavioral burden, and it discloses key conditions: only publicly disclosed committee members are returned, and if not public, the agency's explanation is returned. It also instructs the agent to include a collegiate-system statement; this exceeds what the schema alone would reveal, though error cases and permissions are not covered.

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 three short, front-loaded sentences with no filler. It covers the main content, the fallback behavior, and the output instruction, so every sentence earns its place.

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 tool with no output schema and no annotations, the description adequately covers the returned data and the public-disclosure fallback. It is incomplete, however, because it does not define the two required parameters and does not distinguish this tool from the many committee-related siblings, so an agent could still select the wrong tool or pass malformed identifiers.

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 0%, so the description must compensate, but it never explains what unit_id and job_number mean, what formats they take, or how they identify the case. The description only hints at '案' and '機關', leaving parameter interpretation to inference from the parameter names.

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 identifies the specific resource ('某一案的採購評選委員名單') and the fields returned (姓名、現職、學經歷), which makes the core purpose clear. It loses one point because it does not explicitly differentiate itself from overlapping siblings such as search_committee_members or committee_member.

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 phrase '某一案' plus the required unit_id and job_number implies the tool is for retrieving a specific case's committee list. However, there is no explicit guidance about when to prefer this tool over the many committee-related siblings, and no exclusions or alternatives are named.

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