generate_sample_data

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the write-oriented nature (generate and insert), the required insert+batch permissions, and that permission control is enforced by CallToolRequest — meaningful context beyond the schema. However, it fails to disclose the potentially destructive behavior of the overwrite option, effects on existing rows, or transaction/rollback behavior, which matters for a data-mutating tool.

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 front-loads the purpose in the first sentence, which is good. However, the third sentence ("完整 inputSchema 同上(Permission 控制由 CallToolRequest 强制执行)") is largely redundant: it restates that the schema is available and partially repeats the permission requirement already given in sentence two. One or two of the three sentences earn their place; the third does not.

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?

This is a complex tool — three parameters, one of which is a deeply nested options object with a rule-matching engine — yet the description is only three short sentences. With 0% schema publication coverage, no output schema, and no annotations, the agent is left without information about how rules work, what overwrite does, what the return value looks like, or how generation is scoped. The description is not complete enough for an agent to call this tool confidently without opening the raw schema and guessing at semantics.

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 compensate for parameter semantics, but it only hints at tableName via "根据表结构." The complex nested options object — including rules with match conditions (tableName, columnName, columnType, columnNamePattern), seed, columns, overwrite, and columnOverrides — is left entirely unexplained by both the schema and the description. The line "完整 inputSchema 同上" merely points back to the schema and adds no semantic value.

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 states a specific action and resource: "根据表结构自动生成并插入样例数据" (automatically generate and insert sample data based on table structure). The verb (generate + insert) and the resource (sample data for a table) clearly convey what the tool does and distinguish it from read-only siblings like get_sample_data. However, it does not name any sibling explicitly, so differentiation is implicit rather than stated.

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?

No guidance is given on when to use this tool versus alternatives such as get_sample_data, execute_batch, or execute_query. The only contextual hint is the permission requirement (insert+batch), which reads as a precondition rather than usage direction. There are no exclusions, alternatives, or recommended scenarios provided.

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