find_category

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

With no annotations, the description carries the full burden and does disclose the key behavior: fuzzy matching returns similar categories on partial matches, and matching is level-based with priority. It also tells the agent the return is category codes. It omits whether results are paginated or how many candidates typically come back, which keeps it from a 5.

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 step label and the core instruction are front-loaded, but the parenthetical Korean sentence largely restates the English text and the rocket emoji adds no information. Roughly a third of the text is duplicated bilingual content.

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 two-parameter lookup with no output schema, the description covers the input rule (Korean), the matching behavior (fuzzy, level-priority), and the nature of the output (category codes) well enough to call it correctly. The exact shape of returned records is left unstated, which is a minor gap.

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 100%, so both parameters are already documented including the Korean query examples and max_results default. The prose adds only the Korean-input emphasis already present in the schema, so the baseline 3 applies.

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?

States a specific verb and resource ('find shopping categories', 'find category codes'), and positions itself as a prerequisite step for the datalab tools. It stops short of naming an individual sibling, so the distinction from datalab_shopping_category and friends is inferred from the 'STEP 1' framing rather than spelled out.

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 'STEP 1' prefix plus 'required for datalab tools' gives a clear sequencing rule: call this first to get codes, then feed them downstream. The Korean-only query constraint is a useful usage condition. There is no explicit when-not guidance or named alternative, so it is not a 5.

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