list_columns

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

With no annotations, the description carries the full burden of explaining behavior. It conveys a read-style operation that returns column names and types, but it does not explain how the source is resolved, what happens with the default source, or whether errors are possible.

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 focused sentence that states the action and expected result without filler. For a simple listing tool, this is appropriately concise and front-loaded.

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 tool is simple and an output schema exists, so the description does not need to explain return values in detail. However, the source parameter is undocumented and no relation to sibling tools is provided, so the agent still has to make assumptions about the only input and when this tool is preferable.

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%, and the description never mentions the 'source' parameter. The phrase '数据集的' only indirectly hints that source identifies the dataset, leaving the only parameter's semantics largely implicit.

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 ('列出' / list) and a specific resource ('数据集的全部列名与类型' / all column names and types of the dataset). It is clear about the primary intent, though it does not explicitly differentiate itself from close siblings like get_schema or preview_data.

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 about when to use this tool versus alternatives such as get_schema, preview_data, or sql_query. No prerequisites, limitations, or exclusions are mentioned, so the agent must infer the appropriate usage context.

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