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NAJEMWEHBE

unreal-ai-connection

bulk_inspect_assets

Inspect multiple assets in a single call, returning per-path data and aggregate counts. Isolates partial failures; useful for pipeline audits such as verifying texture power-of-two compliance.

Instructions

Inspect multiple assets in one MCP call by composing the inspect_asset C++ handler bridge-side. Returns per-path inspection data plus aggregate counts; partial failures isolated per result. Mirrors the bulk_*_assets family shape. Use for pipeline audits (e.g. enumerate 500 textures and report which lack a power-of-two source).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathsYesAsset object paths to inspect (each non-empty, NUL + '..' segments rejected).
continue_on_errorNoDefault true. When false, stop at first per-path failure and return the partial results.
Behavior4/5

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

Discloses that partial failures are isolated per result, and returns per-path data plus aggregate counts. Without annotations, this is valuable behavioral context. Could further mention that it is read-only, but the inspection nature implies safety.

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

Conciseness5/5

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

Three well-structured sentences with front-loaded purpose, output summary, and an example use case. Every sentence adds value without redundancy.

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

Completeness4/5

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

Given the tool's simplicity and no output schema, the description adequately covers purpose, output shape, error behavior, and a typical use case. It could briefly mention the return format structure, but it remains functionally complete.

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

Parameters3/5

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

Input schema has 100% coverage with descriptions for both parameters. The description adds context about 'partial failures isolated per result' relating to continue_on_error, and 'per-path inspection data' relating to paths, but does not significantly augment the schema's explanations.

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 that the tool inspects multiple assets in one call, distinguishing it from the singular inspect_asset sibling. It also mentions the bulk_*_assets family, reinforcing its role as a batch operation.

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

Usage Guidelines4/5

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

The description provides an explicit use case (pipeline audits for textures lacking power-of-two sources), implying batch scenarios. However, it does not explicitly state when not to use it (e.g., for single asset inspection), leaving a small gap.

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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