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Dynamic Tables Describe Iceberg Table

dynamic_tables_describe_iceberg_table
Read-onlyIdempotent

Retrieve schema, catalog integration, and external volume details for an Iceberg table to understand its structure and storage configuration.

Instructions

Describe schema, catalog integration, and external volume of an Iceberg table.

Input Schema

NameRequiredDescriptionDefault
databaseNoQuote names that aren't all uppercase, exactly as list tools return them.
table_nameYesQuote names that aren't all uppercase, exactly as list tools return them.
schema_nameNoQuote names that aren't all uppercase, exactly as list tools return them.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv3.0.0
    • addedInput schema / properties / database / description
      Added value: +"Quote names that aren't all uppercase, exactly as list tools return them."
    • addedInput schema / properties / schema_name / description
      Added value: +"Quote names that aren't all uppercase, exactly as list tools return them."
    • addedInput schema / properties / table_name / description
      Added value: +"Quote names that aren't all uppercase, exactly as list tools return them."
  2. Addedv2.0.4

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered by structured data. The description adds only which metadata facets are returned, which partly duplicates the output schema; it gives no information about authorization requirements, behavior for malformed or missing tables, or latency.

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?

A single front-loaded sentence with no filler. It is efficient, though it is arguably too thin for a tool whose name is triply redundant with its title and whose sibling set is large.

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?

An output schema exists and annotations cover safety, so the description doesn't need to explain return values. However, for a tool sitting among several describe-style siblings in a Snowflake-like catalog, the lack of any routing or prerequisite information leaves a real gap for correct invocation.

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% and each of the three parameters carries the quoting guidance, so the schema does the heavy lifting. The description contributes nothing about database/schema_name defaults or nullability semantics; baseline 3 applies.

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?

States a specific verb (Describe) and a precise resource (Iceberg table) plus the facets returned: schema, catalog integration, external volume. This distinguishes it from generic table describers by naming the Iceberg-specific content, though it never explicitly contrasts with tables_describe_table or dynamic_tables_describe_dynamic_table.

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 usage context is only implied: call this to inspect an Iceberg table's structure and storage wiring. There is no statement of when to prefer it over tables_describe_table, dynamic_tables_describe_dynamic_table, or the list_iceberg_tables sibling, and no prerequisites (e.g., catalog integration must already exist).

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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