List the distinct values in a column (for enum/value discovery — e.g. what statuses or service types exist). Returns each value with its row count, most common first.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max distinct values to return (default 50). | |
| table | Yes | Table name. | |
| column | Yes | Column name. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false and closed-world scope, so safety is covered. The description adds behavior the annotations do not: results are ranked most-common-first and each value carries a row count, which tells the agent how to interpret and rely on ordering.
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?
Two sentences, zero padding: the first states the operation and its discovery use case, the second states the return shape. Both are front-loaded with the essential noun (distinct values in a column) before the supporting detail.
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 read-only, three-parameter tool with full schema coverage and no output schema, the description supplies the missing return-shape context (values plus counts, sorted). Only minor gaps remain, such as how truncation from limit behaves, but nothing critical for correct invocation is absent.
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%, including the limit default of 50 and the table/column meanings, so the schema carries the parameter burden and a 3 is the baseline. The description adds only the 'most common first' ordering nuance and no per-parameter detail 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 states a specific verb and resource ('List the distinct values in a column') and adds the purpose ('for enum/value discovery — e.g. what statuses or service types exist'), which implicitly separates it from describe_schema and run_sql. It never names a sibling tool explicitly, so an agent must infer the boundary rather than being routed to it.
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 gives a clear when-to-use context: discovering enums or value sets such as statuses or service types, including what the output looks like for that purpose. There are no explicit exclusions or named alternatives, so the agent is not told when to prefer run_sql or describe_schema instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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