update_statistics

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

With no annotations, the description carries the responsibility of explaining behavior. It discloses that the tool executes UPDATE STATISTICS, is unsupported on read-only SQL Analytics Endpoints, and details the fullscan/sample_percent interaction. It does not mention permissions or broader side effects, but the SQL operation and parameter behaviors are clearly conveyed. This is solid but not exhaustive behavioral disclosure.

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 organized with a short purpose statement followed by a parameter list, making it easy to scan. The only minor inefficiency is that the SQL Analytics Endpoint restriction appears twice: in the intro and again in the item parameter. Otherwise, every piece of information is useful and appropriately sized.

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 six-parameter tool with no annotations, the description is remarkably complete: it covers all parameters, provides default behavior, explains option interactions, and gives environment restrictions. Since an output schema exists, not explaining return values is acceptable. An agent has enough context to select and invoke this tool correctly without additional lookup.

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 fully compensate. It explains all six parameters, including workspace and item identifiers, qualified_table format, stat_name, and the precedence between fullscan and sample_percent. The description adds meaning well beyond the bare schema titles and would allow an agent to construct valid arguments confidently.

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: 'Update an existing statistic via UPDATE STATISTICS.' It identifies the resource (statistic) and the SQL operation, and the word 'existing' distinguishes it from create_statistics and delete_statistics siblings. This is more than a tautology and gives an agent a precise mental model of the tool.

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 explicitly limits usage to Data Warehouses and warns that SQL Analytics Endpoints are rejected, which gives clear when-not-to-use guidance. It does not explicitly name alternative sibling tools such as create_statistics or show_statistics, but the phrase 'existing statistic' implies the update-versus-create distinction. This is strong contextual guidance, falling 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.