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Snowflake Drop Schema

snowflake_drop_schema
Destructive

Drop a Snowflake schema with a required confirmation flag to prevent accidental deletion.

Instructions

Drop a schema in Snowflake. Requires confirmation flag.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
confirmNo
databaseNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed6 schema fields changedv1.2.0
    • addedInput schema / additionalProperties
      Added value: +false
    • removedInput schema / properties / confirm / title
      Removed value: -"Confirm"
    • removedInput schema / properties / database / title
      Removed value: -"Database"
    • removedInput schema / properties / name / title
      Removed value: -"Name"
    • removedInput schema / title
      Removed value: -"snowflake_drop_schemaArguments"
    • removedOutput schema / title
      Removed value: -"snowflake_drop_schemaDictOutput"
  2. First observedv0.1.0

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true and openWorldHint=true, so the safety profile is covered by structured data. The description adds one useful behavioral detail beyond annotations — that a confirmation flag is required — but omits what actually gets destroyed (contained tables/views), whether the drop is cascading or irreversible, and recovery options.

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?

Two short sentences, front-loading the core action and the confirmation requirement with zero padding. It is efficient, though the extreme brevity comes at the cost of substance rather than trimming waste.

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?

For a destructive, irreversible schema drop with three undocumented parameters and no meaningful schema coverage, the description is too thin. An output schema exists so return values need no explanation, but the missing detail on scope, irreversibility, and the confirm/database parameters leaves real gaps.

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 coverage is 0% and no parameter has a description, so the description carries the full burden. It only alludes to the 'confirmation flag' (confirm), leaving its default-false semantics and behavior undefined, and the `database` parameter is not mentioned at all.

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 states a specific verb and resource ('Drop a schema in Snowflake'), so the operation is unambiguous. It does not differentiate itself from siblings like snowflake_create_schema or snowflake_undrop_schema, but the name and verb make the action clear without opening the schema.

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?

It notes a confirmation requirement but gives no when-to-use guidance, no prerequisites or permissions, and never mentions alternatives such as snowflake_undrop_schema for recovery. The agent must infer usage context entirely.

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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