get_issue_distribution

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

With no annotations, the description carries the full burden of behavioral disclosure. It usefully discloses the sorting order ('由多到少'), the scope ('申論真實考點'), and the optional filter. However, it does not explain data sources, whether counts are unique questions, or how the optional filter affects the output, so transparency is partial.

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 compact sentence that leads with the core purpose ('爭點熱度排行'), then explains the basis, ordering, and filtering in one breath. Every phrase adds useful information with no redundancy.

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, has only one optional parameter, and an output schema exists, so the description does not need to detail return values. Still, it lacks guidance on parameter value semantics and does not clarify how this tool relates to the many sibling tools, leaving some context-dependent decisions to the agent.

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 for the bare parameter definition. It does communicate that the single parameter is an optional sub-subject filter ('可選子科目篩選'), which adds meaning beyond the schema. It does not, however, define what a sub-subject is or how values should be formatted.

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 that this tool provides a ranking of exam issues by how often they appear, sorted from most to least frequent, and specifies the scope as essay questions on real points of contention (學說/實務交鋒點). It is more specific than a generic 'get distribution' label, though it does not explicitly differentiate itself from the similar sibling get_topic_distribution.

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 gives no guidance on when to use this tool versus alternatives such as get_topic_distribution, get_statute_frequency, or search_by_issue. It only mentions an optional sub-subject filter, leaving the selection context entirely implicit.

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