Skip to main content
Glama

set_output_format

Configure render output format and file path in Blender for 3D modeling and animation projects. Choose from PNG, JPEG, OPEN_EXR, TIFF, or BMP formats.

Instructions

Set the render output format and optionally the output file path.

Args: format: Output format. One of: PNG, JPEG, OPEN_EXR, TIFF, BMP. filepath: Optional output file path. Must be an absolute path.

Returns: Confirmation dict with the new output settings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatYes
filepathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions that the tool sets output format and filepath, but does not disclose behavioral traits such as whether changes are persistent, if they affect existing files, what permissions are needed, or how the confirmation dict is structured. The description is minimal beyond the basic action.

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 core purpose in the first sentence, followed by structured sections for Args and Returns. Each sentence earns its place by providing essential information without redundancy, making it highly efficient.

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?

Given that there is an output schema (implied by 'Returns: Confirmation dict'), the description does not need to detail return values. It covers the tool's purpose and parameters adequately for a configuration tool, but lacks behavioral context like persistence or side effects, which is a minor gap given the tool's likely low complexity.

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 description coverage is 0%, so the description must compensate. It adds meaning by specifying the allowed values for 'format' (PNG, JPEG, OPEN_EXR, TIFF, BMP) and clarifying that 'filepath' is optional and must be an absolute path, which goes beyond the schema's basic type definitions. However, it does not explain default behaviors or constraints beyond the enum list.

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's purpose with a specific verb ('Set') and resource ('render output format and optionally the output file path'), distinguishing it from sibling tools like 'render_image' or 'export_file' that handle actual rendering or exporting operations.

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

Usage Guidelines3/5

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

The description implies usage when configuring render output settings, but does not explicitly state when to use this tool versus alternatives like 'set_render_resolution' or 'set_render_engine', nor does it mention prerequisites or exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/HoldMyBeer-gg/blend-ai'

If you have feedback or need assistance with the MCP directory API, please join our Discord server