Retrieve column-level statistics for an Impala table, including distinct values, nulls, and max/avg size, to assess data distribution and query planning.
Column-level statistics: distinct values, nulls, max/avg size (SHOW COLUMN STATS).
| Name | Required | Description | Default |
|---|---|---|---|
| db_name | Yes | ||
| table_name | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds context about what statistics are included and the SQL command, but it does not disclose any additional behavioral traits such as permission requirements, limitations, or performance characteristics.
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, front-loaded sentence with no filler. Every part adds value: the resource type, the specific statistics returned, and the underlying command.
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 read-only tool with two self-explanatory parameters, an output schema, and strong annotations, the description is largely complete. It could be slightly richer by explicitly stating that statistics are reported per column or by noting any table prerequisites, but the current definition is sufficient for correct selection and invocation.
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 does not explain db_name or table_name, their format, or their relationship to the results. The parameter names are self-explanatory enough to avoid a score of 1, but the description adds no parameter-level meaning to compensate for the missing schema descriptions.
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 identifies the resource (column-level statistics) and the specific content returned (distinct values, nulls, max/avg size), and it names the underlying command (SHOW COLUMN STATS). The phrase 'column-level' differentiates this from table-level siblings such as get_table_size, get_table_schema, and get_table_preview.
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 usage when column-level statistics such as distinct counts, null counts, or size metrics are needed, but it does not explicitly state when to use this tool versus alternatives or when not to use it. No sibling alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.