snowflake_warehouse_scale_and_execute

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It mentions 'Safely scale up' and 'optionally restore previous size', but does not explain what 'safely' entails (e.g., rollback on failure), the side effects on warehouse size, or what happens if the query fails. The behavior is only described at a high level without specifics an agent would need to understand consequences.

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?

The description is a single, tightly worded sentence. It front-loads the primary action (scale and execute) and mentions the optional restore in a natural way. There is no filler or redundancy, making it highly efficient.

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?

For a composite tool with four parameters and no schema descriptions, the description is skeletal. It omits critical operational details such as what happens when restore_previous_size is false, whether the warehouse remains scaled if the query fails, or any prerequisites (e.g., warehouse must exist). The presence of an output schema is unknown, but the description does not prepare the agent for expected results or error conditions. This is insufficient for reliable autonomous use.

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?

With zero schema descriptions, the tool description must compensate for parameter meaning. It implicitly maps warehouse_name and target_size to 'scale up a warehouse', query to 'run a heavy query', and restore_previous_size to 'optionally restore previous size'. This provides some semantic linkage, but it lacks details such as valid target_size formats, query constraints, or the exact effect of restore_previous_size on failure. It is enough for a superficial understanding but insufficient for precise invocation.

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?

The description clearly states the tool's composite purpose: scale a warehouse, run a query, and optionally restore size. It uses specific verbs and resources, and the 'Composite recipe' label distinguishes it from single-action sibling tools like snowflake_resize_warehouse or snowflake_query. However, it does not explicitly contrast itself with these alternatives, so it stops short of a perfect 5.

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?

The description provides no guidance on when to use this tool versus sequentially calling separate tools like resize and query. It does not mention any conditions, prerequisites, or alternative scenarios. The only implicit hint is 'Safely', but no explicit when-to-use or when-not-to-use guidance is given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.