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weijie-tan3

Trino MCP Server

by weijie-tan3

describe_table

Retrieve column names, data types, and metadata for a Trino table. Pass the table name, with optional catalog and schema.

Instructions

Describe the structure of a table (columns, types, etc).

Args: table: The table name (e.g. 'my_table'). Preferably just the table name; catalog and schema should be passed as separate parameters. Fully qualified names like 'catalog.schema.table' are also accepted. catalog: The catalog name (optional if default is configured) schema: The schema name (optional if default is configured)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesThe table name (e.g. 'my_table'). Preferably just the table name; catalog and schema should be passed as separate parameters. Fully qualified names like 'catalog.schema.table' are also accepted for convenience.
schemaNoThe schema name (e.g. 'my_schema')
catalogNoThe catalog name (e.g. 'my_catalog')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

There are no annotations, so the description carries the full burden. It only states the purpose and parameter guidance, but does not disclose whether this is a read-only operation, any permission requirements, error behavior, or what happens if the table doesn't exist. Though 'describe' implies a safe read, that is not explicit.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficient: a one-sentence purpose followed by a structured Args list. It is front-loaded and easy to scan. However, the Args section duplicates the schema's parameter descriptions, which is somewhat redundant but not overly verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is relatively simple, and the output schema is present, so return values are covered. Parameters are well-documented in both schema and description. The main gap is missing usage guidance and behavioral details, which makes it only minimally complete for such a tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 largely repeats the schema's parameter docs, with the same wording for 'table' and similar descriptions for 'catalog' and 'schema'. The only slight addition is the note 'optional if default is configured', which adds minor nuance but also potential ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states what the tool does: 'Describe the structure of a table (columns, types, etc).' The verb and resource are specific. It does not explicitly distinguish from sibling tools like show_create_table or get_table_stats, but the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage through its purpose and parameter details, but it does not explicitly state when to use this tool compared to alternatives such as show_create_table or list_tables. No exclusions or alternative recommendations are provided.

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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