get_view_columns

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

Without annotations, the description carries the burden of behavioral disclosure. It mentions using 'sys.columns' (a system view) and returns metadata, implying read-only behavior but does not explicitly state safety, permission requirements, or error conditions. Some transparency is provided by the implementation note but it is not comprehensive.

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 extremely concise with no extraneous words. It front-loads the purpose in the first sentence, uses a clear Args section, and every sentence adds value. Perfect structure for an MCP tool.

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?

The description covers the purpose, parameter details, and compatibility context. Since an output schema exists, it need not explain return values. It is complete for a simple metadata retrieval tool, though it could mention more about potential errors or required permissions.

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 has 0% description coverage, so the description must compensate. It adds meaning by describing each parameter's type (name or GUID) and provides an example for qualified_name. This clarifies usage beyond the raw schema.

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 action 'Return column metadata' and the resource 'SQL view', which distinguishes it from sibling tools like get_table_columns. The purpose is specific and unambiguous.

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 implicitly indicates when to use the tool (when needing column metadata for a view) and mentions compatibility with both Fabric Data Warehouses and SQL Analytics Endpoints. However, it does not explicitly contrast with alternative tools like get_table_columns or provide when-not-to-use guidance.

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