klax_get_review_queue

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

No annotations are provided, so the description carries the behavioral burden. It discloses the local-storage read nature, explicitly states no KLAS call is made, and explains that an empty result means nothing is due today. It does not cover auth or side effects, but '조회' and local lookup strongly imply a safe read.

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?

Three short sentences with no filler. The main verb and resource appear first, and the local-storage qualifier and empty-result explanation each add meaningful value.

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 optional-parameter read tool, the description covers purpose, data source, filtering behavior, and empty-result semantics. An output schema exists, so return structure does not need to be repeated in the description.

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?

The input schema has zero description coverage, so the description compensates by explaining that course_id is optional and filters results to that course. This is sufficient for the single simple parameter.

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 verb ('조회합니다' – retrieves), a specific resource (forgetting-curve review queue items), and the as-of-today scope. It also distinguishes this tool by noting it is a local-storage lookup with no KLAS call, separating it from server-backed siblings.

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 makes the usage context clear: use it for today's review queue items and optionally filter by course_id. However, it does not explicitly name alternative tools or state when not to use it, so the guidance remains implied rather than explicit.

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