klax_get_attendance_status

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

With no annotations provided, the description carries the full burden. It does disclose an important behavioral trait: the risk score is a heuristic based on the general rule that 1/3 absences result in an F, and it explicitly disclaims being the school's official determination. However, it does not mention whether the operation is read-only, requires authentication, or how current the data is, so the disclosure 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 compact and well-structured: the first sentence states the core purpose and scope, and the second sentence provides an important caveat about the risk calculation. Every sentence earns its place with no filler or 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?

An output schema exists, so return-value details do not need to be described. However, the description lacks parameter semantics, usage timing, and any behavioral context beyond the risk disclaimer. For a simple required 'course_id' call an agent may still proceed, but 'yearhakgi' and 'verbose' semantics are missing, making the description only partially complete.

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. It only loosely maps to 'course_id' through '특정 과목', but gives no explanation of 'yearhakgi' (year/semester) or 'verbose'. These parameters remain ambiguous, which is a significant gap for a low-coverage 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 states a specific action ('조회하고' / query and analyze) on a specific resource ('특정 과목의 전자출결 현황' / attendance status for a specific course), and adds a distinctive output element: absence risk analysis. This clearly differentiates it from sibling tools like klax_get_timetable or klax_get_overview.

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 when the tool is useful—when a user needs attendance status for a course—but it provides no explicit guidance about when to choose this tool over siblings, no exclusions, and no mention of prerequisites such as an active session or semester context. Usage context is only implied, not stated.

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