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

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds real behavior: AND semantics across all listed columns, reverse-index matching, dtype/org narrowing, and n capped at 20. It does not explain what 'group' does or what happens for zero matches, so it is strong rather than complete.

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?

Content is dense and front-loaded, with the routing rule first and details second. The Korean/English duplication doubles the length, but each version is tight and every sentence carries information.

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 read-only search tool with an output schema (so return values need not be re-explained), the definition covers the filtering semantics, the query constraint, and the result cap. The unexplained 'group' parameter is the one remaining 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 0%, so the description must carry the load. It explains names (all columns required), dtype/org narrowing, and n's maximum of 20, which is genuine added meaning — but the 'group' boolean parameter is never mentioned, leaving one of five parameters undocumented anywhere.

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+resource ('Find datasets with ALL given columns') and immediately contrasts itself with the sibling search tool. It also names the distinguishing constraint (no topic, query fixed to empty string), so an agent can tell it apart from search without opening either schema.

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?

Explicit when-to-use ('no topic', query pinned to empty string) and an explicit alternative ('for a topic use search(query, fields=...)'). Routing is unambiguous.

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