course_report

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

No annotations exist, so the description bears the full burden: it states side effects (saves a Markdown skeleton to reports/) and the return value (saved path and structure). It also clarifies that title doubles as the filename. It does not discuss overwrite or directory-creation behavior, but the key behaviors are disclosed.

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?

One functional sentence followed by a tight bullet list; every line adds needed information not present in the schema. The side effect and return value are front-loaded.

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 4-parameter generation tool with no annotations and an output schema, the description covers purpose, all parameters, storage location, and return content. Minor gaps like overwrite semantics and whether reports/ is auto-created keep it from being fully exhaustive.

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%, and the description compensates by documenting every parameter: title as title+filename, course_name, student default placeholder, and sections with a 1–8 range that is absent from the schema. This adds real meaning beyond the raw property names and types.

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 names a specific verb ('生成'), a precise resource ('课设报告 Markdown 骨架'), the target directory, and the return value. This is sufficient to distinguish it from siblings like scaffold_project or paper_search, even without naming them explicitly.

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 intended use is clear from the imperative first sentence, but the description gives no explicit when/when-not guidance or comparison with sibling tools such as scaffold_project. It stops at purpose and leaves alternative selection to inference.

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