describe_column

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

Annotations already provide safety profile (readOnly, idempotent, non-destructive). The description adds valuable behavioral details: it returns data type, nullability, default, LLM description, and both outgoing and incoming foreign key directions. No contradictions.

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?

Three sentences with no fluff. First sentence states purpose and key output, second gives alternative, third provides composition pattern. Every sentence adds value.

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 one parameter, full annotations, and an output schema (present, though not detailed here), the description covers the tool's purpose, output, and usage flow comprehensively. No missing information.

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 single parameter 'qualified_name' is well-described in the schema (100% coverage). The description adds extra guidance on the format (e.g. 'public.orders.user_id') and a prerequisite hint to call describe_table first if needed, exceeding baseline 3.

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's verb ('drill into') and resource ('one column'), and distinguishes it from the sibling 'describe_table' by specifying it works on a single column with a three-part qualified name.

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?

Explicitly states when to use this tool ('when you need to drill into one column'), when to use the alternative ('Use describe_table instead when you want the whole table'), and provides a common composition pattern ('chain describe_table to describe_column').

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