list_statistics

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

With no annotations provided, the description must carry the behavioral burden. It clarifies that both Data Warehouses and SQL Analytics Endpoints are supported and describes the filtering semantics for schema, table, user_only, and auto_only. However, it does not disclose whether the tool is read-only, how the boolean filters interact, or any access requirements. For a listing operation this is somewhat sufficient, but not fully transparent.

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 with a one-line summary, a supported-resources note, and a clean Args list. It is front-loaded with the core purpose and contains no filler or redundant statements. Every sentence contributes useful information.

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 six parameters, the supported resource types, and the filtering behavior, which is enough to invoke the tool correctly. An output schema is present, so not describing return values is acceptable. The main gap is the lack of guidance on how this tool relates to show_statistics and other statistic-related siblings, which would improve contextual completeness.

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 schema has 0% description coverage, so the description must fully compensate for parameter semantics. It does: each parameter is explained with meaningful details such as 'Workspace name or GUID,' 'unqualified name' for table, and the exact filtering behavior for user_only and auto_only. This goes well beyond the bare schema names.

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's function: 'List statistics on a warehouse or SQL Analytics Endpoint.' The verb 'list' and the resource scope are specific, and the supported resource types are spelled out. However, it does not differentiate this tool from the sibling 'show_statistics' tool, so an agent may need additional context to choose between them.

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 explains what the tool does and what parameters filter results, but it does not provide guidance on when to use this tool versus alternatives like show_statistics, create_statistics, or other statistics tools. No when-to-use or when-not-to-use guidance is given.

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