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NAJEMWEHBE

unreal-ai-connection

inspect_data_asset

Inspect a UDataAsset via its package path. Returns class, parent, package path, and editable properties with types and values; handles errors with ok=False.

Instructions

Shallow-reflect a UDataAsset by package path and return class, parent class, package path, and editable property list (name, Python type, stringified value). SYNTHETIC bridge-side handler (PR #92 language-shim experiment): composes execute_unreal_python + get_log_lines via the marker pattern. Property values for nested structs / arrays / dicts are stringified as 'container:type' or '' — no recursion. Logical errors (asset not found, marker buffer overflow, payload unparseable) return as ok=False success envelopes; transport-level errors return as JSON-RPC errors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesPackage path to a UDataAsset asset, e.g. /Game/Data/DA_PlayerStats. Must be a non-empty string.
Behavior5/5

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

The description extensively covers behavior: shallow reflection, non-recursive stringification of nested types, error modes (logical vs transport), and synthetic composition of other tools. With no annotations, this fully informs the agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is detailed and informative, but slightly verbose with implementation details (PR #92, marker pattern). However, it is well-structured with clear sections for purpose, behavior, and error handling.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description adequately explains return fields (class, parent class, path, property list) and error handling. It covers enough context for an agent to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, providing a clear description of the 'path' parameter. The tool description adds context about its use for UDataAsset and the shallow reflection process, enhancing understanding beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a shallow reflection on a UDataAsset, returning specific fields. It distinguishes from sibling tools like inspect_asset or inspect_data_table by specifying the target type and shallow nature.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for UDataAsset inspection but lacks explicit guidance on when to choose this tool over alternatives like inspect_asset or other specialized inspectors. No when-not-to-use or alternative recommendations.

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

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