get_table_columns

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

No annotations provided, so the description must disclose behavioral traits. It indicates a read operation (returning metadata) and mentions compatibility, but does not explicitly state permissions, side effects, or other constraints.

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 concise, front-loaded with the core purpose, and structured with an Args section. No unnecessary words.

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 simplicity of the tool and presence of an output schema, the description covers the main aspects: what it does, on which platforms, and parameter meanings. It could mention that the table must exist, but overall it is adequate.

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 fully explains each parameter: workspace, item, and qualified_name, including the format for qualified_name with an example (dbo.sales). This adds essential meaning.

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 returns column metadata for a SQL table via sys.columns, and specifies it works on both Fabric Data Warehouses and SQL Analytics Endpoints. This distinguishes it from siblings like get_view_columns and get_cluster_columns.

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 provides clear context by specifying the resource type (SQL table) and platforms, but does not explicitly state when to use this tool over alternatives. However, the sibling differentiation is implicit through naming.

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