columns_find

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

No annotations are provided, so the description carries the burden of disclosing behavior. It states what is searched and hints at the searchable attributes, but it does not disclose return format (though an output schema exists), pagination, or any side effects (which are unlikely for a search). Given the output schema exists, the return behavior might be inferred, but the description alone is minimal. It doesn't contradict any annotations, so a 3 is appropriate for a non-destructive search 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?

The description is a single, concise sentence that immediately states the scope and search criteria. It is front-loaded with the key information (what it does and where), and there is no wasted wording. It effectively serves as a clear summary for an agent.

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 search tool with an output schema, the description covers the core functionality. However, it could mention the purpose of the 'native_type' filter or any nuances like case sensitivity or wildcard support, which are not in the schema descriptions. The presence of an output schema reduces the need to explain return values, but the description could still provide more context on search behavior. Overall, it's adequate but with minor gaps.

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?

The schema covers 67% of parameters: 'query' and 'native_type' have descriptions in the schema (query: 'Words to match...', native_type: 'Classify | Date | Verbatim...'), leaving 'limit' with only a default and no description. The tool description adds a bit of context by mentioning 'name, purpose, or prompt text' which aligns with the 'query' parameter, but it doesn't add details about 'limit' or 'native_type' beyond the schema. With 67% coverage, the description partially compensates but not fully, so a 3 is fair.

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 ('find') and resource ('columns across all 24 tables'), and specifies the search criteria ('by name, purpose, or prompt text'). This clearly distinguishes it from sibling tools like table_describe or table_read, which focus on reading table content or structure. The scope ('all 24 tables') adds precision, so an agent can quickly understand what this tool does.

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 implies usage for searching columns across the entire dataset, which is clear enough. However, it does not explicitly contrast with siblings like table_describe (which might describe a single table) or vault_search (which might search broader content). There are no explicit 'when to use' or 'when not to use' instructions, but the context is sufficient for a simple search tool.

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