Find columns

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

Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds cross-schema scope and the 'every table that carries it in one call' behavior, but it does not mention limits, ordering, or result shape; this is useful but not rich behavioral context.

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?

Two tightly written sentences front-load the core capability, then add a targeted usage rationale with a concrete example. Every clause earns its place; there is no filler.

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 two-parameter search tool with safety annotations, the description is largely complete: it states scope, optional filter, and the intended efficiency benefit. There is no output schema and the exact return format is implied rather than stated, but an agent can infer it will see the matching columns and tables.

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 description coverage is 100%, with clear definitions for name and the optional type substring. The description's 'optionally filtered by type' and customer_id example mirror the schema rather than adding new semantic meaning, so the baseline 3 applies.

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 opens with a specific verb and resource: 'Search for columns by name across every schema, optionally filtered by type.' It clearly distinguishes the tool from sibling listing tools by emphasizing cross-schema column search rather than table or schema enumeration.

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?

It gives explicit guidance to use this instead of listing tables when the database is large, with a concrete customer_id example. It does not spell out exclusions relative to describe_table or table_relationships, so it stops short of a full when/when-not matrix.

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