create_struct

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

With no annotations, the description carries the full disclosure burden. It richly documents the expected input format (field dicts, allowed types, worked example) but says nothing about creation side effects, such as whether an existing struct is overwritten, whether the new asset is auto-saved, or whether the target path must already exist. The format transparency is high, but the consequences of the operation are undisclosed.

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 logically organized (purpose, concept, args, allowed types, KB reference, example) and front-loaded with a one-line purpose statement. The final example call with an empty fields list is the weakest element—trivial and partially redundant with the fields example above—but it does not materially bloat an otherwise economical definition.

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 moderate-complexity creation tool with an output schema, the description covers purpose, parameter formats, allowed types, and even points to a KB document. It still omits creation semantics (overwrite/save behavior, path requirements) and any exclusions, leaving an agent to guess at the operation's consequences. Adequate, but with clear gaps.

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%, and the description compensates well: fields gets the exact dict structure [{"name": ..., "type": ...}], the full allowed field-type list, and a concrete example, while struct_name gets a realistic naming example ('S_PlayerData'). The path param is only glossed as 'Content browser path,' leaving its exact format unspecified, though the schema supplies a sensible default ('/Game/Data').

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?

Opens with a specific verb+resource, 'Create a custom Struct asset,' and reinforces the purpose with a one-sentence definition of what a struct is (grouping related variables into a single data type). The resource type is distinct enough from siblings like create_enum and create_data_table, though it never names them explicitly, which keeps it from a 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 line 'making it easy to pass multiple values as one parameter' implies the use case for a struct, giving an agent conditional context for selecting the tool. However, there is no explicit when-to-use vs. alternatives guidance, even though siblings like create_enum and create_data_table occupy adjacent data-asset territory. The usage signal is present but left to inference.

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