count_table_rows

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

With no annotations provided, the description carries the full behavioral disclosure burden. It reveals the exact query mechanism (`SELECT COUNT_BIG(*)`), the time-travel behavior via `OPTION (FOR TIMESTAMP AS OF ...)`, and the supported platforms. This is meaningful behavioral context beyond the bare input schema, though it could go further on performance or permission implications.

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 well-structured and front-loaded with the core purpose. The Args section is compact and every line adds necessary information—parameter meanings, format examples, and time-travel behavior. No filler or redundancy.

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 all parameters, supported platforms, and optional time-travel behavior, which is sufficient for a fairly simple count tool. An output schema exists, so return-value details need not be described. It stops short of explicitly addressing the sibling `count_view_rows` case, which would have made it fully 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%, so the description fully compensates. Every parameter is explained with its meaning and format: `workspace` as name/GUID, `item` as warehouse or SQL endpoint name/GUID, `qualified_name` with a `dbo.sales` example, and `as_of` with ISO-8601 semantics and exact query behavior. This is strong value 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 a specific action—return the total row count of a table—and the exact SQL mechanism (`SELECT COUNT_BIG(*)`). It is unambiguous about the resource type (table) but does not explicitly distinguish itself from the sibling `count_view_rows`, so it misses full sibling differentiation.

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 gives useful context: it works on both Fabric Data Warehouses and SQL Analytics Endpoints, and it explains when to use or omit the `as_of` parameter for time-travel counts. However, it does not provide explicit guidance on when to use this tool versus alternatives like `count_view_rows` or `read_table`.

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