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ChrisChoTW

databricks-mcp

by ChrisChoTW

get_table_schema

Retrieve the complete structure of Databricks tables, including column definitions and extended metadata, to understand data organization and relationships.

Instructions

Get table structure (DESCRIBE EXTENDED)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
catalog_nameYes
schema_nameYes
table_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The get_table_schema tool implementation, registered with @mcp.tool, validates identifiers and executes a DESCRIBE EXTENDED SQL query.
    @mcp.tool
    def get_table_schema(ctx: Context, catalog_name: str, schema_name: str, table_name: str) -> List[Dict[str, Any]]:
        """Get table structure (DESCRIBE EXTENDED)"""
        catalog = safe_identifier(catalog_name, "catalog_name")
        schema = safe_identifier(schema_name, "schema_name")
        table = safe_identifier(table_name, "table_name")
        return execute_sql(ctx, f"DESCRIBE EXTENDED {catalog}.{schema}.{table}")
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'DESCRIBE EXTENDED', hinting at a detailed output, but doesn't clarify if this is a read-only operation, what permissions are required, whether it's cached, or any rate limits. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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

Conciseness5/5

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

The description is extremely concise and front-loaded, consisting of a single, efficient phrase: 'Get table structure (DESCRIBE EXTENDED)'. Every word earns its place by conveying the core purpose and hinting at the output detail, with zero waste or redundancy.

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?

Given the tool's moderate complexity (3 required parameters) and the presence of an output schema, the description is minimally adequate. The output schema likely covers return values, reducing the need for description detail. However, with no annotations and 0% schema coverage for inputs, the description should do more to explain parameter semantics and usage context to be fully complete.

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

Parameters1/5

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

The description adds no meaning beyond what the input schema provides. With 0% schema description coverage, the three required parameters (catalog_name, schema_name, table_name) are undocumented in both the schema and description. The description doesn't explain what these parameters represent, their formats, or examples, failing to compensate for the schema's lack of documentation.

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 the tool's purpose as 'Get table structure (DESCRIBE EXTENDED)', which includes a specific verb ('Get') and resource ('table structure'). It distinguishes itself from siblings like 'get_table_detail' or 'get_table_history' by focusing on schema/structure rather than metadata or lineage. However, it doesn't explicitly differentiate from 'search_tables' or 'list_tables', which could also relate to table information.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to choose 'get_table_schema' over 'get_table_detail', 'get_table_history', or 'search_tables', nor does it specify any prerequisites or exclusions. The agent must infer usage from the tool name and context alone.

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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