get_enum_values

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

No annotations are provided, so the description carries the full behavioral disclosure burden. However, it does not mention the limit/truncation behavior (default 50, max 100) despite claiming 'all unique values', and does not mention includeCount effects. This is a notable gap and mildly misleading without the schema's qualification.

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 two sentences with no filler: purpose first, followed by use case and a concrete example. Every sentence contributes.

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 the schema covers all parameters, so the description's use-case and example are mostly sufficient. However, with no output schema and no annotations, it omits the return format and the important caveat that results are truncated at the limit, which prevents a fully complete picture.

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%, so the baseline is 3. The description adds helpful context for columnName by giving enum-type examples, but it does not meaningfully elaborate on tableName, limit, or includeCount beyond the schema.

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 specific verb ('获取' – get) and resource ('指定列的所有唯一值' – all unique values of the specified column), and elaborates with the use case (enum columns like status/type/category) and a concrete example (orders.status → pending, shipped, delivered). This clearly differentiates it from query/sample tools among the sibling tools.

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?

It explicitly states when to use it: to understand all possible values of enum-type columns and to craft accurate WHERE conditions. It does not name alternatives or exclusions, but the context is unambiguous enough for an agent to select it over execute_query or get_sample_data.

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