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blender_batch

Batch image and mesh export operations.

Instructions

Batch image and mesh export operations.

Operations:

  • resize: resize images matching pattern (default *.png)

  • convert: convert image formats in input_dir

  • export: export mesh objects whose names contain name_pattern

Return Format

Standard dict with keys: success, message, data

Examples

await call_tool("blender_batch", {"operation": "resize", "input_dir": "C:/images"})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
widthNo
heightNo
patternNo*.png
input_dirNo
operationNoresize
output_dirNo
name_patternNo
export_formatNoglb
source_formatNojpg
target_formatNopng

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Addedv0.5.0

TDQS

C2.7/5.0
Behavior2/5

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

Annotations are all false, so the description carries the burden of disclosing side effects. It does not state whether files are overwritten, whether a Blender session is required, or any limitations. The operations imply file writes and modifications, but no explicit behavioral disclosure is provided.

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 appropriately concise: an intro, a three-item bullet list, a return format line, and a code example. It is well-structured and front-loads the main purpose, with no unnecessary verbosity.

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 10 parameters and three distinct operations, the description is too sparse. It lacks per-operation parameter mapping, prerequisites, and edge-case behavior. The standard return format and output schema existence do not compensate for the missing operational detail.

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?

With 0% schema coverage, the description must compensate. It explains 'pattern' defaulting to *.png and 'name_pattern' for export, but leaves unclear key parameters like width/height, source_format/target_format, and output_dir. The example demonstrates input_dir usage, but many params remain semantically opaque.

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 'Batch image and mesh export operations' and enumerates three specific operations (resize, convert, export), which defines a concrete scope. It differentiates from siblings like blender_export by focusing on batch and multi-type operations, though it doesn't explicitly contrast each mode.

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?

No explicit guidance on when to use this tool versus alternatives is given. The name implies batch use, and the operation list suggests scenarios, but there is no mention of exclusions or when to prefer a sibling like blender_export or script_execute.

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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