get_schema

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It indicates a read-only introspection operation returning schema statistics and examples, which is useful, but it does not mention behavior around the optional source parameter, defaults, caching, cost, or side effects.

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 concise sentence, front-loaded with the core action and followed by a compact, well-structured enumeration of returned details. Every word earns its place and there is no filler.

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?

The presence of an output schema means return values do not need to be fully re-described, and the single optional parameter keeps the tool simple. However, the unexplained 'source' parameter and absence of any usage context or sibling differentiation leave meaningful gaps for an agent deciding how to invoke or route the tool.

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 only parameter, 'source', has no schema description (0% coverage), and the tool description never mentions it or explains what values it accepts or how the default behaves. The agent is left to infer the meaning of 'source' and 'default' from the parameter name alone.

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 opens with a clear verb+resource pair ('获取数据集详细 Schema') and enumerates specific output contents: column names, types, non-null counts, mean/quantiles, and value examples. This distinguishes it from a simple column listing, though it does not explicitly name sibling tools or contrast itself with them.

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 should be used when detailed schema and statistical summaries are needed, but it gives no explicit guidance on when to choose this over siblings like list_columns, preview_data, or aggregate_stats. There are no stated exclusions or alternative recommendations.

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