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render_final

Render approved Blender scenes into final frames or MP4 videos on JANCTION GPUs, then poll status and download results before 24-hour deletion.

Instructions

Render the final frames (or a video) of a Blender scene on JANCTION GPUs.

Call this after the user approved a preview. Pass scene_id from render_preview (or scene_path / scene_script to upload a new .blend / bpy script). frame_start..frame_end are inclusive; several frames are split across GPUs and joined into output.mp4 (output='mp4', fps), a single frame gives a PNG (output='png'; 'auto' picks). Returns job_id and a time estimate right away; the render runs in the background: poll with render_status, then fetch with render_download. Inputs and results are deleted 24 hours after last use, so download them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fpsNo
widthNo
cameraNo
heightNo
outputNoauto
samplesNo
scene_idNo
frame_endNo
scene_pathNo
frame_startNo
scene_scriptNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses that the call returns job_id plus an estimate immediately while rendering runs in the background, prescribes polling with render_status followed by render_download, and warns that inputs/results are deleted 24 hours after last use.

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?

Front-loaded with the core action, then workflow and retention caveats, with no filler sentences. Dense but every clause carries information; minor density cost from packing the polling chain into one sentence.

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?

An output schema exists, so return values need not be detailed, and the description still explains the async return contract and lifecycle. The only gap is the four undocumented rendering parameters, which an agent may set blindly given the defaults.

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 coverage is 0% across 11 parameters, so the description must compensate. It gives meaning for scene_id, scene_path, scene_script, frame_start/frame_end (inclusive), output ('mp4'/'png'/'auto') and fps, but leaves width, height, camera and samples entirely undocumented in both description and schema.

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?

States a specific verb (render) and resource (final frames or video of a Blender scene) plus the execution environment (JANCTION GPUs). The phrase 'Call this after the user approved a preview' cleanly separates it from the sibling render_preview.

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

Usage Guidelines5/5

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

Explicitly states when to call it (after preview approval) and names the alternative entry points: reuse scene_id from render_preview, or upload via scene_path/scene_script. It also routes the agent forward to render_status and render_download, so the full workflow is inferable without opening other definitions.

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