get_warehouse_credit_usage

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

No annotations, so description carries full burden. It explains what the tool does and what output to expect (total credits per warehouse, split). Does not mention side effects but for a read-only aggregation tool this is sufficient. Could be more explicit about the scope (all warehouses, only active?).

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?

Two sentences plus an Args block. Front-loaded with purpose, no wasted words. Efficiently conveys all necessary information.

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?

Given the simplicity (one param, output schema exists), the description covers purpose, usage context, and parameter. Could briefly note that it returns per-warehouse data, but output schema likely handles details. Missing maybe a note about data freshness or caching.

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 coverage is 0% so description must explain parameters. The one parameter 'lookback_days' is clearly described: 'How many days back to look (default from server config, typically 7).' Provides default behavior and typical value.

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?

Clearly states verb 'get' and resource 'warehouse credit usage'. Specifies aggregation per warehouse and split into compute vs cloud services. Distinguishes from siblings like find_expensive_queries or list_warehouses.

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?

Provides usage context: 'Use this to see where spend is concentrated before drilling into individual warehouses or queries.' Implies a hierarchical analysis workflow. Does not explicitly mention when not to use, but context signals suggest alternatives exist.

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