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NAJEMWEHBE

unreal-ai-connection

get_selected_actors

Retrieves name, label, class, and transform of actors selected in Unreal Editor's World Outliner or viewport. Enables an AI to observe selected objects before applying Python scripting.

Instructions

Return name/label/class/transform of every actor currently selected in the editor's World Outliner / viewport. Companion to apply_python_to_selection — lets the LLM observe what is selected before running code against it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided; description carries full burden. It states the exact output (name/label/class/transform of every selected actor). While it doesn't discuss edge cases like empty selection, the read-only nature 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.

Conciseness5/5

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

Two sentences, front-loaded with core functionality, zero wasted words. Efficient and clear.

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 zero parameters and no output schema, the description fully covers the tool's inputs, outputs, and the intended usage pattern as a companion to another tool. No gaps identified.

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?

No parameters exist, so schema coverage is 100%. Description adds nothing beyond the empty schema, but baseline for 0 parameters is 4 per guidelines.

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?

Description clearly states the tool returns selected actors' properties (name/label/class/transform). It distinguishes from siblings like 'get_actors_in_level' by specifying selection context.

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?

Explicitly frames the tool as a companion to 'apply_python_to_selection', guiding the agent to use it before acting on selections. Does not list exclusions or alternatives but provides clear context.

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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