snowflake_resume_dynamic_tableResume scheduling for a Snowflake dynamic table and monitor its refresh lag to restore automated updates and catch delays.
Resume scheduling and lag monitoring for a dynamic table.
| Name | Required | Description | Default |
|---|---|---|---|
| database | No | ||
| table_name | Yes | ||
| 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 / schema_name / titleRemoved value: -"Schema Name"Input schema / properties / table_name / titleRemoved value: -"Table Name"Input schema / titleRemoved value: -"snowflake_resume_dynamic_tableArguments"Output schema / titleRemoved value: -"snowflake_resume_dynamic_tableDictOutput"v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare idempotentHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds that resuming reinstates scheduling and lag monitoring, which is useful behavioral context, but it omits required state, side effects on existing data, and latency of resumption.
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 filler and the action front-loaded. The phrasing 'resume scheduling and lag monitoring' is slightly ambiguous about what exactly is resumed, but it is efficient overall.
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?
Wrong — see below.
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% across three parameters: database, schema_name, and table_name. The description mentions no parameters at all, so it does not compensate for the coverage gap — it neither clarifies that database/schema_name override the session default nor explains qualified-name handling.
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 (resume) and resource (dynamic table), plus what resuming restores: refresh scheduling and lag monitoring. An agent can distinguish it from suspend/refresh siblings by the verb alone, though no sibling is named explicitly.
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 resume versus using snowflake_refresh_dynamic_table or snowflake_describe_dynamic_table, no statement that the table must currently be suspended, and no prerequisites or permission hints. The agent must infer the operating context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.