count_view_rows

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

No annotations are provided, so the description carries full burden. It describes the SQL operation (COUNT_BIG) and time-travel option, but does not explicitly state that it is read-only or disclose any potential side effects or performance impacts. Implied transparency is moderate.

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 action, and uses clear formatting. Every sentence adds value without excess.

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?

With an output schema present (though not shown), the description handles the main purpose well. It lacks mention of error conditions or permissions, but for a simple count tool, it is largely complete.

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 0%, but the description fully explains all four parameters: workspace, item, qualified_name (as dot-separated), and as_of (with ISO-8601 format and time-travel semantics). This adds substantial meaning beyond the 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 tool returns the total row count of a view using COUNT_BIG. It identifies the specific resource (view) and operation (count rows), differentiating it from siblings like count_table_rows.

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 notes it works on Fabric Data Warehouses and SQL Analytics Endpoints and explains time-travel usage via as_of. However, it does not explicitly contrast with alternatives like count_table_rows or mention when not to use it.

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