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Tables Describe Table

tables_describe_table
Read-onlyIdempotent

Retrieve column definitions, data types, nullability, and primary keys for a Snowflake table or view to inspect its schema before writing queries.

Instructions

Describe column definitions, data types, nullability, and primary keys for a table or view.

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 and destructiveHint=false, so the safety profile is covered and the description only needs to add context. The enumeration of returned metadata (types, nullability, keys) adds some value, but since an output schema exists it is largely redundant, and nothing is said about permissions, visibility of objects the user cannot access, or cost/latency of the lookup.

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?

A single sentence that front-loads the verb and the resource and lists the return payload in a compact clause. There is no filler or repetition.

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

Completeness4/5

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

With an output schema covering return values and annotations covering safety, the description is nearly complete for a simple metadata-read tool. The remaining gap is qualification semantics (how database, schema_name and table_name combine) and the boundary against DDL/sample alternatives, but nothing essential to correct invocation is missing.

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 database/table_name/schema_name already carries the quoting guidance, so the baseline is 3. The description adds nothing about parameter semantics — in particular it does not explain the database/schema qualification relationship or whether schema_name defaults to the session schema.

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 resource ('table or view') and enumerates exactly what metadata is returned: column definitions, data types, nullability, primary keys. An agent can immediately tell it is a metadata-read tool, though it does not distinguish itself from nearby siblings such as tables_get_table_ddl or recipes_inspect_table_with_sample, which plausibly surface overlapping 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?

There is no explicit when-to-use or when-not-to-use guidance and no alternative named. The phrase 'for a table or view' only weakly implies scope (it covers views as well as tables), leaving the agent to infer why it would pick this over tables_get_table_ddl or databases_get_database_ddl.

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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