cx_list_courses

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

With no annotations, the description carries the behavioral burden and does a solid job: it discloses role-dependent behavior (student vs teacher) and explains the significance of the returned IDs. It does not mention authorization or side effects, but for a list operation these are less critical. This exceeds the minimum by adding meaningful behavioral context.

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 concise sentence that front-loads the primary action and result. It includes the essential payload (three IDs) and the downstream purpose without wasted words. Every clause contributes useful information.

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 parameterless list tool with an output schema, the description covers the necessary context: what is listed, how results differ by role, and why those results matter for later operations. There are no missing parameters to explain, and the output schema handles return structure. The description leaves no critical gap for an agent to call this tool correctly.

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 tool has zero parameters, so the baseline is 4; the schema already fully covers parameter needs. The description adds value by clarifying the output IDs and their role in future operations, though there are no parameters to describe. No parameter semantics gap exists.

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 uses a specific verb '列出' with a clear resource '学习通课程' and distinguishes student vs teacher returns. It also names the exact IDs returned (courseId/clazzId/cpi), making the tool's purpose unambiguous. This clearly differentiates it from general list tools.

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 this is the starting point for all course-related operations by stating that subsequent operations depend on the three IDs. However, it does not explicitly mention when to use this over the sibling cx_s_list_learning_courses or provide exclusion criteria. Usage is reasonably inferable but not made explicit.

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