create_statistics

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

No annotations are provided, so the description carries the disclosure burden. It explains the Fabric single-column limitation, the SQL Analytics Endpoints read-only restriction, and the fullscan/sample_percent override interaction. It does not discuss permissions, overwrite behavior, or failure modes, but it covers the most material behavioral 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 front-loaded with the core purpose and key limitations, then organized into a clear Args block. Each parameter receives one concise line. The slight repetition of the SQL Analytics Endpoints restriction is acceptable because it appears at both overview and parameter-specific levels.

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?

For a create operation, the description covers platform support, supported statistic type, parameter semantics, and scan/sample behavior. An output schema exists, so return-value details are not required here. The remaining gaps, such as duplicate-handling and permission requirements, are minor compared to the completeness of the provided context.

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 must compensate. It documents all seven parameters, adds practical meaning (workspace name or GUID, warehouse selectivity, qualified table example, sample_percent overrides fullscan), and clarifies how fullscan and sample_percent interact 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 opens with a specific verb and resource: 'Create a single-column statistic on a table.' It immediately distinguishes itself from sibling statistics tools (list/update/delete/show) by stating the single-column scope and the Data Warehouse target. The purpose is 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 gives clear when/where context: only Data Warehouses are supported, SQL Analytics Endpoints are read-only and rejected, and only single-column statistics are possible. It does not name alternative tools such as update_statistics or show_statistics, so it falls just short of explicit alternative routing.

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