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render_preview

Render a preview image of Blender objects to inspect shape, proportions, normals, and materials. Auto-frames objects, creates a camera, renders with EEVEE, and returns the image path.

Instructions

Render a preview image and return its absolute path.

THEN OPEN THAT IMAGE AND LOOK AT IT. Read the returned image_path with your file reading tool, or call read_preview_image. Geometry statistics cannot tell you whether an asset has the right shape, sensible proportions, correct normals or a material that reads properly -- only the picture can.

Auto-frames the given objects, creates an AI_PreviewCam if the scene has no camera, renders with EEVEE at 512x512 by default, and restores the scene's render settings afterwards. Images land in workspace/previews.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoSquare resolution. 512 is the fast default; go to 1024 only for a final check.
labelNoShort label used in the filename, e.g. 'crate_v2'
cameraNoRender from this camera instead of the active one
engineNo
marginNo
objectsNoObjects to frame automatically. Omit and set frame_all=true to fit everything visible.
samplesNoMore samples means less noise and a slower render
filenameNoExact filename stem; overrides label
directionNoViewing angle when auto-framing
frame_allNoFrame every visible object when `objects` is omitted
transparentNoTransparent background
resolution_xNo
resolution_yNo
restore_cameraNoPut an existing camera back where it was after framing. A camera the bridge created stays put.
view_transformNoColour management for this render. 'Standard' (the default here) shows the colours the materials actually specify; Blender's usual 'AgX' desaturates heavily and makes materials hard to judge. The scene's own setting is restored afterwards.Standard

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it delivers. It discloses auto-framing, AI_PreviewCam creation when no camera exists, EEVEE rendering at 512x512 by default, restoration of render settings, and output location (workspace/previews). It also clarifies camera restore behavior. This is thorough and transparent.

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?

The description is front-loaded with the purpose and a clear imperative to inspect the image, then details the workflow and side effects. Every sentence adds value—auto-framing, camera handling, default engine and size, restore behavior, and output location. It's efficient and well-structured without redundant text.

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 tool with 15 parameters and no output schema, the description covers the essential workflow and side effects. It mentions the return path, output location, and restoration behavior. It doesn't explain all enum options (direction, engine) but those are self-explanatory or documented in the schema. It lacks explicit info about return structure beyond the path, but that's minor given the tool's nature.

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 coverage is 73%, so the schema already documents most parameters. The description adds some context (e.g., the view_transform note about 'Standard' vs 'AgX'), but it doesn't systematically explain parameters beyond what the schema provides. Given high schema coverage, the baseline of 3 is appropriate; the description doesn't significantly compensate for the 27% gap.

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 clearly states the tool's purpose: 'Render a preview image and return its absolute path.' This is a specific verb+resource pairing. It doesn't explicitly differentiate from sibling render_turntable, but the name and context make the distinction clear, so it's not fully distinguishing.

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?

The description provides explicit guidance on when and how to use the tool: 'THEN OPEN THAT IMAGE AND LOOK AT IT. Read the returned image_path with your file reading tool, or call read_preview_image.' It also explains that geometry statistics are insufficient, and names an alternative tool (read_preview_image). This is strong usage guidance with 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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