add_lesson

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

With no annotations, the description must disclose behavioral traits. It adds a specific rule about mindmap seeds: '默认不生成、例外才有', and clarifies that skipping it is not penalized ('不写不罚'). However, it does not disclose other operation behaviors such as return values, error handling, or permanent side effects, leaving partial transparency.

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 coherent single paragraph with the purpose front-loaded and the nuanced policy following. Each sentence earns its place, though a more structured bullet-point format could improve scannability. The date '2026-07-21 定' adds minor context but is not essential.

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 relatively complex (9 params, nested objects, no output schema, no annotations). The description covers the core purpose and a key optional-parameter policy, but does not explain return values, error behavior, or the meaning of required fields like order and content_markdown. This leaves the description moderately complete but not fully informative.

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 description adds meaningful guidance for the modality_declarations.mindmap parameter by explaining when to configure it (only when structure clarity is needed) and that leaving it empty is acceptable. This goes beyond the schema's simple description. However, it does not clarify the semantics of several undocumented parameters like order, title, content_markdown, and estimated_minutes, so it only partially compensates for the 56% schema coverage.

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 begins with '为指定 course 添加一节 lesson', clearly stating the action (add) and target (a lesson to a specified course). It also provides usage context with 'agent 备课时用', which helps distinguish it from lesson-update tools like update_lesson.

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 phrase 'agent 备课时用' explicitly indicates when to use the tool, giving a clear usage context. It does not name alternative tools or specify when-not-to-use scenarios, but the creation-oriented context is sufficient; the mindmap policy is more about parameter selection than tool selection.

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