schema_search

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 only implies a read-only search operation and does not mention result size limits, case sensitivity, whether schema-qualified names are supported, or what the output contains. This is a notable gap for an unannotated 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 compact and front-loads the core behavior in the first sentence. The second sentence adds a use case but is somewhat redundant with the first, keeping it from a perfect score.

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 simple two-parameter search tool, the core usage is clear. However, with no output schema, the description does not explain what the search returns or any limits, so an agent may be unsure about the result format without additional inference.

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 input schema already documents both parameters fully, including the LIKE pattern format and the tables/columns enum with a default. The description adds little beyond 'matching a pattern,' so the baseline score of 3 is appropriate.

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 and resource: search for tables or columns matching a pattern. This is clear enough to identify the tool's job, though it does not explicitly differentiate it from siblings like list_tables or describe_table.

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 gives some guidance by saying it is 'useful for finding tables by name,' which implies a name-based discovery use case. However, it does not explicitly say when to prefer this tool over alternatives such as list_tables, describe_table, or query, and it provides no exclusions.

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