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gen_prepare_import_manifest

Validate and normalize asset import manifests for Unreal Engine, ensuring correct paths and settings before importing generated assets.

Instructions

Validate and normalize a generated asset import manifest for Unreal.

KB: see knowledge_base/31_GENERATIVE_CONTENT_PIPELINE.md#import-manifest-helper Example: gen_prepare_import_manifest(task_id="tripo_task_123", local_files=["C:/Gen/slime.glb"], content_path="/Game/Generated/Enemies")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idYes
providerNotripo
asset_nameNo
local_filesNo
content_pathNo/Game/Generated
create_blueprintNo
overwrite_existingNo
create_material_instanceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description alone must disclose side effects, yet it only says 'validate and normalize.' It does not state whether the tool writes a manifest, overwrites files, requires permissions, or mutates project state, and the overwrite_existing parameter hints at possible side effects that are left unexplained.

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 core sentence is front-loaded and compact, with a KB pointer and a realistic call example that illustrate usage. Every line earns its place, though the lack of parameter or behavior detail limits how informative the overall text is.

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

Completeness2/5

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

With eight parameters, zero schema descriptions, and no annotations, the description is insufficient for an agent to invoke the tool correctly without consulting external docs. The output schema exists, but parameter semantics, side effects, and placement in the pipeline are all missing.

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

Parameters2/5

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

Schema description coverage is 0% and the description does not compensate. The example demonstrates task_id, local_files, and content_path values, but the remaining five parameters are functionally undocumented in both the schema and description. No parameter-level meaning is added beyond what names and defaults already show.

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

Purpose4/5

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

The description opens with 'Validate and normalize a generated asset import manifest for Unreal,' a specific verb+resource pair that clearly identifies the tool's job. It does not explicitly name sibling tools such as gen_tripo_import_to_project, so differentiation is implied rather than stated.

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 example and KB reference imply this is a preparation step in the generative asset pipeline, but the description never states when to use it versus gen_tripo_import_to_project or validate_import_result. Usage context is present only via the example and the 'generated asset import manifest' phrasing.

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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