Get table column details including DuckDB types, nullability, null counts, and sample values to understand data structure and quality.
Columns of a table with DuckDB type, nullability, null count and sample values.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| kind | Yes | ||
| name | Yes | ||
| source | Yes | ||
| columns | Yes | ||
| row_count | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool read-only, idempotent, and non-destructive, so no safety disclaimer is needed. The description adds value by specifying the exact returned information, which aligns with the read-only behavior, but it does not disclose edge cases like behavior when the table does not exist.
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 compact sentence, front-loaded with 'Columns of a table' and every phrase adds information about the returned data. There is no filler or repetition.
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 one-parameter read-only introspection tool, the description covers the main purpose and output, and the presence of an output schema fills in the return structure. However, it misses explicit parameter-to-role mapping and usage boundaries, so it is not fully complete.
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 schema offers only a bare 'name' string with no description, and schema description coverage is 0%. The description mentions 'a table' but never explicitly states that the 'name' parameter is the table name or what format it should take, leaving the parameter role under-specified.
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 (a table) and the specific column metadata returned (DuckDB type, nullability, null count, sample values), which distinguishes it from siblings like list_tables and sample_rows. However, it is a noun phrase rather than an explicit verb phrase, 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?
No guidance is given on when to use describe_table versus alternatives such as profile_table or sample_rows. The description only states what the tool outputs, leaving the agent to infer the appropriate invocation context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.