klax_write_study_note_html

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

With no annotations, the description carries the full burden. It discloses that the tool does not call LLM/API, only renders HTML, rejects saving if locators are not in the index, and writes a local file. This is thorough behavioral disclosure for a mutation 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?

Three sentences in Korean, front-loaded with the main purpose, then behavioral details. Each sentence adds value with no redundant wording.

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 nested note parameter and the output schema presence, the description covers the note structure, validation behavior, and local write. It could mention error cases beyond locator rejection, but that is minor.

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 compensate. It details the required structure of the note object (title, overview, sections with title, explanation, why_it_matters, source_locators) and gives locator examples. It does not explain course_id or output_path, but their names are self-explanatory.

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 states a specific verb (save), a concrete resource (local single HTML study note), and a distinguishing process (validating source locators before saving). This clearly separates it from siblings like klax_generate_study_guide_html, which generates a guide rather than persisting a pre-built note.

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 provides clear context: it is for saving a structured note after the model writes it, and it explicitly notes that it does not call LLM/API, implying it is a local renderer. However, it does not explicitly name alternatives or state when not to use it.

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