snowflake_list_functionsList user-defined functions (UDFs) in a Snowflake database or schema, optionally filtered by pattern, to inventory reusable SQL logic.
List user-defined functions (UDFs) in a database or schema.
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | No | ||
| database | No | ||
| schema_name | 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 / properties / schema_name / titleRemoved value: -"Schema Name"Input schema / titleRemoved value: -"snowflake_list_functionsArguments"Output schema / titleRemoved value: -"snowflake_list_functionsDictOutput"v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the agent knows this is a safe, non-mutating read. The description adds the scoping constraint (database or schema) but nothing about filtering behavior, result ordering, or limits, so it adds only modest value beyond structured fields.
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 short sentence with no wasted words, and the resource and scope are front-loaded. It is appropriately sized for a simple list tool, though brevity here also means the parameter gaps go unaddressed.
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, and annotations cover the safety profile. However, with three undocumented parameters (notably 'pattern') and no usage guidance, the definition stops short of what an agent needs to invoke it confidently.
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% for all three parameters. The phrase 'database or schema' vaguely maps to the 'database' and 'schema_name' parameters, but the 'pattern' parameter is entirely unexplained in both schema and description — the description does not say it is a naming filter or what syntax it accepts.
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 (user-defined functions/UDFs) with an explicit scope of 'a database or schema'. It does not differentiate itself from related siblings such as snowflake_list_procedures or snowflake_describe_function, which an agent would have to infer.
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?
No guidance on when to use this tool versus alternatives like snowflake_list_procedures or snowflake_describe_function, and no prerequisites or context for selecting it. Usage is only implied by the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.