list_departments

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

No annotations provided, so description carries burden. Mentions 'snapshot' implying read-only read, but does not explicitly state that it is non-destructive or what the snapshot entails. Could be more transparent about behavior.

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?

Description is compact, front-loaded with purpose, then parameter, then return fields. Slightly dense due to code encoding details, but still concise overall.

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?

Given one parameter and an output schema, description covers the core: purpose, parameter usage, return fields. Could elaborate on 'snapshot' meaning or limitations, but adequate for the tool's simplicity.

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 0%, but description fully explains the query parameter: default empty, filters by official department name substring, and gives examples ('財務', '法律'). Adds meaning beyond the 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?

Clearly states the tool lists department codes (snapshot) and distinguishes from siblings like search_courses and get_syllabus by specifying the resource (department codes) and the operation (list).

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?

Provides guidance on using the query parameter for filtering by official department name substring, with examples. Also hints that the code can be fed to search_courses. Lacks explicit when-not-to-use scenarios.

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