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ue5_save_asset

Save a specific Unreal Engine asset to disk. Skip clean packages with optional dirty-only mode to prevent unnecessary writes.

Instructions

Save an asset to disk; only_if_is_dirty=true skips clean packages. Saves are scoped to the asset's own package — this tool never triggers a whole-project save. | 保存资产落盘(only_if_is_dirty=true 仅脏包写盘;作用域=该资产包,绝不全工程保存)。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asset_pathYesAsset path, e.g. /Game/BP_Test | 资产路径
only_if_is_dirtyNoSkip clean packages (default false) | 仅脏包写盘

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv3.2.1
    • addedInput schema / properties / asset_path / description
      Added value: +"Asset path, e.g. /Game/BP_Test | 资产路径"
    • addedInput schema / properties / only_if_is_dirty / description
      Added value: +"Skip clean packages (default false) | 仅脏包写盘"
  2. First observedv3.2.0

TDQS

A3.9/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full behavioral burden. It does disclose meaningful traits: writes to disk, only_if_is_dirty skips clean packages, and saves are scoped to the asset's own package. It does not mention failure behavior or whether an asset must be loaded first, but the core behavioral profile is clear.

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 English portion is compact, front-loaded, and contains no filler. The Chinese repetition of the same information adds length and does not provide new semantics for an AI agent, so it prevents a perfect conciseness score.

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?

For a simple two-parameter save operation with no output schema, the description covers the essential behavior: what is saved, the dirty-check condition, and the scope boundary. It is complete enough for an agent to invoke correctly, though return or error behavior is not described.

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?

Schema description coverage is 100%, so the baseline is 3. The description reinforces only_if_is_dirty semantics and adds the package-scoping guarantee, but it does not add meaningful detail about asset_path beyond what the schema's example already provides.

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 opens with a specific verb and resource ('Save an asset to disk') and immediately clarifies the scope: it saves only the asset's own package and never triggers a whole-project save. This makes the tool's purpose unambiguous and distinguishes it from global save or build operations among the siblings.

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 context by explaining the dirty-only save option and the single-package scope, but it never explicitly states when to prefer this tool or names an alternative for project-wide saves. The 'never triggers a whole-project save' statement is a useful exclusion, but the when-to-use guidance is left mostly implicit.

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