snowflake_list_schemasList schemas in a Snowflake database or the active database, optionally filtered by pattern, to discover available structures before writing SQL.
List all schemas within a specific database or the current active database.
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | No | ||
| database | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v1.2.0Input schema / additionalPropertiesAdded value: +falseInput schema / properties / database / titleRemoved value: -"Database"Input schema / properties / pattern / titleRemoved value: -"Pattern"Input schema / titleRemoved value: -"snowflake_list_schemasArguments"Output schema / titleRemoved value: -"snowflake_list_schemasDictOutput"v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, destructiveHint=false, so safety is covered. The description adds the meaningful behavioral detail that omitting a database falls back to the current active database, but says nothing about result shape, limits, or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single compact sentence with the scoping behavior front-loaded and no filler. It is efficient, though slightly terse given the undocumented 'pattern' parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be described. However, with two parameters at 0% schema coverage and 'pattern' unexplained anywhere, the definition is not fully complete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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. It explains the 'database' parameter (specific vs. current active) but never mentions the 'pattern' filter parameter, leaving half the inputs undocumented in both schema and description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (list) and resource (schemas) plus the scoping model (a specific database or the current active database). It is inferably distinct from create/drop/clone schema siblings, but does not explicitly differentiate itself from them or from snowflake_describe_schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied: call it when you need schema names and either pass a database or rely on the active one. No explicit when-not or alternative routing (e.g., use describe_schema for details) is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.