klax_list_learning_materials

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does disclose that the operation reads a local SQLite index (not remote), and enumerates the status values (pending/processing/completed/failed/unsupported). However, it omits what happens for materials that failed or are unsupported, whether any authentication is needed, and what the returned payload looks like. Adequate but minimal for an annotation-free tool.

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?

Two short sentences with no wasted words. The core purpose is front-loaded in the first sentence, and the filtering behavior is stated in the second. It is efficient and scannable.

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 is present, so return-value documentation is covered elsewhere. The description conveys the tool's scope (local index), the status taxonomy, and the filter behavior, which is the essential context for a list-type tool. The main omission is course_id semantics, but overall this is reasonably 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 does explain status semantics ('if status is specified, filters to only that status') and lists valid status values, which adds meaning beyond the bare schema. But course_id — the only required parameter — is never explained in the description, leaving a gap for the required field.

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?

States a specific verb (조회합니다, 'retrieves') and a precise resource: the locally indexed learning-materials list plus its processing status. It also scopes the operation as a local SQLite query rather than a remote KLAS lookup, which adds clarity. However, it never differentiates itself from the near-identically named sibling klax_list_materials, so the agent cannot reliably tell the two apart.

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 one useful usage signal: it is explicitly NOT a remote KLAS query but a local index lookup, and states that specifying status filters results. But it names no sibling alternatives and gives no guidance on when to choose this tool over klax_list_materials, klax_search_learning_materials, or klax_search_course_materials. The usage context is 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.