list_statistics

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 operation as read-only ('list'), which is accurate, but does not disclose potential side effects, authentication requirements, or rate limits. The output schema exists but is not referenced. Adequate for a listing tool but lacks depth.

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 highly concise: one sentence for the main purpose, one sentence for scope, then a bullet-like Args list. Every sentence adds value with no redundancy. Front-loaded with the core action. Excellent structure for AI consumption.

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 listing tool with 6 parameters (2 required) and an existing output schema, the description covers the essential aspects: what it lists, on what resources, and key filtering options. It does not explain the output schema or error conditions, but the presence of an output schema reduces the need. Missing edge cases like 'what if both user_only and auto_only are true' but overall sufficient.

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?

With 0% schema description coverage, the description compensates well by explaining each parameter: workspace, item, schema, table, user_only, auto_only. It adds meaning beyond the schema's type/title, e.g., that user_only and auto_only filter by creation type. However, it does not clarify interaction between user_only and auto_only (e.g., logical AND or OR), which is a minor gap.

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.' It specifies supported resources and distinguishes from siblings like create_statistics, delete_statistics, and show_statistics (implied by naming). The verb 'list' and resource 'statistics' are 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 mentions that both Data Warehouses and SQL Analytics Endpoints are supported, providing context on valid targets. The parameter explanations (schema, table, user_only, auto_only) indicate when to apply filters, but no explicit guidance on when not to use this tool or alternatives like show_statistics. Lacks exclusions but sufficient for intended use.

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