aggregate_stats

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

No annotations are provided, so the description carries the full burden for disclosing behavior. It only states a high-level grouping/aggregation operation; it does not explain whether the tool is read-only, what output is returned, how grouping is performed, how missing values are handled, or whether a data source is required. The behavior beyond the one-liner is completely undisclosed.

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 short and easy to read, but it is under-specified rather than appropriately concise. A single generic clause leaves out nearly all operational context and does not earn its place as the primary tool definition. There is no structure, examples, or routing 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?

Given that the tool has six optional parameters and no required fields, a one-line Chinese phrase is insufficient for an agent to invoke it with confidence. Although an output schema exists, the description still omits how to choose grouping columns, which aggregation modes are valid, what data source is being aggregated, and how this tool differs from similar analysis tools. Important context is missing.

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 description adds no parameter-level meaning and does not mention agg, group_by, metric, condition, source, or format. Schema descriptions cover 4 of 6 parameters (67%), but format and source remain unexplained, and the description does not compensate for this gap. An agent gets little help from the description in deciding how to set parameters correctly.

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 '按字段分组聚合' conveys a core action of grouping by a field and aggregating, so it is not a pure tautology. However, it does not specify the data resource, the output, or which fields are involved, and it does not differentiate the tool from siblings like sql_query or data_insights. The purpose is clear at a high level but still vague.

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?

There is no guidance on when to use aggregate_stats versus sibling tools such as sql_query, correlation_analysis, or data_insights. The description does not state prerequisites, exclusions, or scenarios that favor this tool. An agent must infer usage entirely from the name and schema.

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