Get Table Stats

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

With no annotations provided, the description must carry the full behavioral disclosure burden. The verb '获取' indicates a non-mutating fetch, and the listed metrics clarify what the operation produces, but there is no mention of cost, freshness, approximation, or permissions.

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 a single, efficiently written sentence that front-loads the core action and follows it with a clear comma-separated list of output categories. There is no filler or redundant wording.

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 simple read-style tool with two required parameters and an output schema, the description is essentially complete for invoking the tool correctly. The only meaningful gap is the absence of explicit guidance for choosing this tool over closely related sibling tools.

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 100%, with 'database' and 'table' already documented as 数据库名称 and 表名称. The tool description adds no parameter-level detail beyond what the schema provides, so it meets the baseline but does not exceed it.

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 uses a specific verb ('获取') and resource ('表的统计信息'), and enumerates concrete output types (行数, 数据大小, 索引大小, 列基数). This is clear and helps distinguish it from generic query/describe siblings, though it does not explicitly name or contrast any sibling.

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 implies the tool is for retrieving table statistics and therefore carries contextual usage guidance. However, it does not state when to prefer this over describe_table or explain_query, nor does it provide any 'when not to use' guidance.

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