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Glama

get_table_metadata

Retrieve schema metadata for a specific Athena table by providing database and table names. Get column details, data types, and table structure for clearer understanding.

Instructions

Get metadata for a specific table

Args: database_name: Name of the database table_name: Name of the table catalog_name: Name of the data catalog

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_nameYes
catalog_nameNoAwsDataCatalog
database_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are present, so the description must carry the behavioral disclosure burden. It only says 'Get metadata,' which implies a read operation, but it does not state read-only behavior, required permissions, error conditions, catalog resolution, or what metadata is returned. The description is not misleading but is shallow on behavioral detail.

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

Conciseness3/5

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

The description is short and front-loads the main purpose in the first line. However, the Args list duplicates information already present in the input schema and does not earn its place by explaining semantics or usage. The text is concise but not optimally structured because the redundant parameter block displaces space that could have been used for behavioral or usage guidance.

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

Completeness2/5

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

Although an output schema exists and reduces the need to document return values, the tool has no annotations, no usage routing, and no behavioral context. For a metadata lookup over a catalog/database/table hierarchy, the description should at least mention the catalog default or relation to list_tables and list_data_catalogs. It is minimally viable but not complete enough for an agent to know the correct invocation context.

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

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but the Args block only provides 'Name of the database/table/data catalog,' which essentially repeats the schema titles and property names. It adds no insight into the hierarchy between catalog, database, and table, nor does it mention that catalog_name defaults to AwsDataCatalog. The parameter documentation is minimal and only slightly more helpful than the schema alone.

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 first sentence states a specific verb and resource: 'Get metadata for a specific table.' It is clear and distinguishable from sibling list_tables, which enumerate tables rather than retrieve metadata for one table. However, it does not explicitly contrast itself with any sibling, so it stops short of full differentiation.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives such as list_tables or get_work_group. The Args section only lists parameter names and does not mention prerequisites, typical call flow, or exclusions. The phrase 'specific table' hints at a use case but does not give actionable routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.