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blender_set_render_settings

Configure renderer settings for Blender scenes: engine, resolution, samples, color management, transparency, motion blur, depth of field, and output options.

Instructions

Configure the renderer: engine, resolution, samples, colour management, transparency, motion blur, depth of field and output settings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dofNoDepth of field: {'focus_object': 'Cube', 'aperture_fstop': 2.8}.
fpsNo
engineNo'eevee' (fast), 'cycles' (physically correct) or 'workbench' (fastest, solid preview).
denoiseNo
samplesNo
gpu_deviceNo
resolutionNo[width, height]
frame_rangeNo[start, end]
max_bouncesNo
output_pathNo
output_formatNo
view_transformNo'AgX' (default filmic), 'Filmic' or 'Standard'.
response_formatNo'markdown' for readable output, 'json' for raw structured data.json
use_motion_blurNo
film_transparentNo
resolution_percentageNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

C2.7/5.0
Behavior2/5

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

Annotations indicate this is a mutating operation (readOnlyHint=false) but not destructive. The description adds no behavioral detail beyond 'configure', such as whether unspecified settings are reset, whether changes persist, or what side effects occur. It does not contradict the annotations, but it also does not enrich them.

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 a single, front-loaded sentence that communicates the core purpose efficiently. It is concise and avoids filler, though the list of settings is somewhat dense and could be structured more clearly.

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

Completeness2/5

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

For a tool with 16 parameters, no output schema, and sparse parameter descriptions, this description is too thin. It does not explain return behavior, defaults, or how the settings affect a subsequent render. An agent would need significant additional inference to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 38%, so the description should compensate by explaining parameter meanings and relationships. It lists broad categories like 'samples' and 'output settings' but does not clarify values, defaults, or how parameters interact. Most of the 16 parameters remain semantically under-specified.

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 uses a specific verb ('Configure') with a clear resource ('the renderer') and enumerates the settings it affects: engine, resolution, samples, colour management, transparency, motion blur, depth of field and output settings. This makes the tool's purpose understandable, but it does not explicitly distinguish it from related siblings like blender_render or blender_set_world.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives such as blender_render, blender_set_world, or blender_set_context. It does not mention prerequisites, typical workflow placement, or when not to use it.

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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