get_table_info

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

There are no annotations, so the description carries the burden of explaining behavior. It conveys that this is a read-only metadata operation ('获取'), but it does not disclose caching behavior despite the forceRefresh parameter implying a cache. Edge cases such as cache staleness are not mentioned.

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 compact, front-loaded with the core action, and contains no filler. Every sentence adds useful information about the tool's purpose and typical usage.

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 metadata-lookup tool, the description is reasonably complete. The schema fully documents both parameters, and the description conveys what the returned information covers. It lacks explicit mention of caching behavior, but overall the agent has enough to invoke it correctly.

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 input schema provides 100% parameter description coverage, so the baseline is 3. The description does not add meaningful information about the parameters beyond what the schema already explains; it mainly describes the tool's output rather than its inputs.

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 clearly specifies a verb ('获取') and a resource ('指定表的详细信息'), and lists the concrete contents: column definitions, indexes, and estimated row count. It does not explicitly differentiate itself from sibling tools like execute_query or get_global_schema, so it stops short of a 5.

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 states its intended use: to gain an in-depth understanding of a table's structure. This gives the agent clear context for when to use it, though it does not explicitly explain when to avoid it or which sibling tool to choose instead.

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