create_aggregate

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

With no annotations, the description fully discloses that the tool builds an aggregate distribution, can write an Object form to avoid simulation, and requires frequency/severity distribution-object cells as prerequisites. It does not mention side effects or permissions, but the core behavior is transparent.

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 well-structured, starting with the main purpose, then explaining methods and options. While slightly verbose with technical details, every sentence adds value and is front-loaded with the core action.

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 tool's complexity (14 parameters, multiple methods, output schema present), the description covers methods, method-specific options, and the alternative sibling tool. It does not detail return format (handled by output schema) or error conditions, but overall sufficiently complete.

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 57%, and the description adds significant context by grouping parameters by method (e.g., density for FFT, intervals/max_p for Panjer, min_limit/max_limit/distribution_shift for MC) and explaining the purpose of as_object, clarifying meaning beyond the schema definitions.

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 verb 'Build' and the resource 'frequency-severity aggregate', specifies the three methods (FFT, Panjer, MC), and explicitly differentiates from the sibling tool create_aggregate_mc by mentioning it as a dedicated shortcut for plain MC sampling.

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 explicit guidance on when to use FFT/Panjer vs MC, explains the benefit of as_object=True for analytic methods, and advises that for plain MC sampling the agent should use create_aggregate_mc instead, offering a clear alternative.

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