Find Tables by Business Term

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

The description reveals that the tool uses multiple evidence sources (glossary, catalog, comments, relationships), implying a read-only discovery operation. However, it omits details on authorization, rate limits, or whether results are truncated, relying on agent inference.

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, compact sentence that front-loads the core action and resources. Every part adds value, with no redundancy or extraneous 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?

Given the tool has six parameters, no annotations, and no output schema, the description fails to provide sufficient context. The agent lacks details on parameter formats, behavior, or expected results, making correct invocation difficult.

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?

With 0% schema description coverage, the description only explains the 'term' parameter implicitly. Other parameters (limit, schema, profile, includeRelated, relationshipLimit) are not mentioned, leaving the agent to guess their meaning from names alone.

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 finds candidate tables based on a business term, using specific sources like glossary and catalog metadata. It distinguishes from sibling tools like ob_find_columns or ob_search_catalog, though 'visible candidate tables' is slightly ambiguous.

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?

No guidance is provided on when to use this tool versus other search or lookup tools. The description only states what it does, without indicating alternative tools or 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.