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ue_render_sequence

Render a Level Sequence with Movie Render Queue in a headless background process to avoid blocking the editor. Configure output format, resolution, and directory using a preset.

Instructions

Renderizza una Level Sequence con la Movie Render Queue, in background.

Gira in un processo UnrealEditor-Cmd headless, non nell'editor aperto: la MRQ in-editor è asincrona e terrebbe l'editor occupato per tutta la durata, senza un modo pulito di attenderla dal bridge. Come per le build, si avvia e si consulta ue_render_status.

Args: uproject: percorso del file .uproject. sequence: la Level Sequence, es. "/Game/Cinematics/LS_Intro". config: preset di Movie Pipeline salvato, es. "/Game/Cinematics/MRQ_Preset". È il modo di scegliere formato, risoluzione e cartella di uscita: senza, la MRQ usa le impostazioni predefinite del progetto e potrebbe non scrivere nulla. map_path: livello da caricare; default quello di avvio del progetto. output_dir: dove cercare i file prodotti; default /Saved/MovieRenders. resolution: [larghezza, altezza]; default [1920, 1080]. force: avvia anche se risulta già un render in corso.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forceNo
configNo
map_pathNo
sequenceYes
uprojectYes
output_dirNo
resolutionNo
engine_rootNo
engine_versionNo
Behavior4/5

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

With no annotations provided, the description carries full burden. It discloses it runs in UnrealEditor-Cmd headless, is asynchronous (start and check status), and warns that without config, output may be missing. It could mention return value or non-destructive nature explicitly.

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 well-structured: first sentence states purpose, then context, then Args list. It is appropriately sized for the complexity, though slightly verbose. Front-loaded with key information.

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

Completeness3/5

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

While it covers purpose, behavioral context, and most parameters, it does not describe the tool's return value (e.g., success indicator, job ID). Given no output schema, this is a gap. It also omits two parameters.

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 has 0% description coverage, so the description adds significant value. It explains 7 of 9 parameters (e.g., config format, resolution default, output_dir default). engine_root and engine_version are undocumented, but coverage is high and explanations are clear.

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 renders a Level Sequence with Movie Render Queue in background. The verb 'Renderizza' and resource 'Level Sequence' are specific, and it distinguishes from sibling tools like ue_render_status by focusing on initiating renders.

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?

It explains the tool runs in a headless process to avoid blocking the editor, and directs to ue_render_status for progress. While it doesn't explicitly list alternatives or exclusions, the context is sufficient for when to use this tool.

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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