search_columns

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

Annotations already communicate read-only, idempotent, non-destructive behavior. The description adds valuable behavioral detail beyond annotations: case-insensitive matching, glob support, and the cross-table scope. It does not contradict any annotation.

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?

A single, well-structured sentence with no filler. The core action, scope, and matching semantics are all front-loaded and immediately actionable.

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's low complexity (one parameter), rich annotations, and presence of an output schema, the description covers the essential invocation details. It lacks explicit guidance on when to choose this over sibling tools, but the simple search nature makes this 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?

The schema has zero description coverage for the 'pattern' parameter, and the description fully compensates by defining how the pattern is interpreted: case-insensitive substring or * / ? glob. This is exactly the semantic information an agent needs to call the tool correctly.

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?

Description states a specific verb ('Find'), a specific resource ('columns'), and a precise scope ('across all tables'), plus matching semantics ('case-insensitive substring or * / ? glob'). This clearly distinguishes 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 intended use is implied: search for column names across any table using a pattern. However, there is no explicit statement of when to use this tool versus alternatives (e.g., describe_table for a single table's columns, or list_tables for tables), and no exclusion criteria.

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