convert_lecture_docx

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

With no annotations provided, the description carries the full burden and delivers comprehensive behavioral transparency. It explains the deterministic nature, no login, no storage, faithful conversion details (formatting retention, table backgrounds, image handling, EMU to px conversion, EMF/WMF limitation). It also outlines the return structures for each mode, including the deterministic_hint for assist mode.

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 about 600 characters and contains all necessary information, but it is somewhat verbose and uses a mixed format of bullet points and paragraphs. The main purpose is front-loaded, but the detailed explanation could be more organized. Still, it is efficient relative to the complexity of the tool.

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?

Given the tool's complexity (multiple modes, multiple output structures, dependencies on other tools like upload_image and save_lecture_frag), the description is remarkably complete. It covers both return types, explains the deterministic_hint, and mentions integration points. The output schema exists, so return values are documented elsewhere, but the description adds necessary context for agent decision-making.

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 coverage is 0%, so the description must add meaning for all 5 parameters, and it does. It explains docx_path as absolute path, course_subject_id as source for KG targets, book_id with default 'CC7S', batch as output prefix defaulting to filename stem, and mode with three options and their contexts. This far exceeds the bare schema.

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 clearly states the tool converts a lecture docx into Tiptap content, KG knowledge points, and image list. It specifies deterministic, zero-login, zero-storage behavior. The multiple modes (assist, auto, cuicui) are explained with their intended use cases, making the purpose unambiguous.

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 explicitly states when to use each mode: default assist for understanding-based mapping, auto only when H3 headings match KG knowledge points (cleaned source). It also provides alternatives for image handling (use upload_image and save_lecture_frag) and clarifies that the tool itself does not upload images. This gives clear guidance on when to use this tool versus others.

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