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create_collection

Create a new collection in Blender to organize objects and scenes. Provide a collection name to set up a container for grouping objects.

Instructions

Create a new collection.

Return Format

Standard dict with keys: success, message, data

Examples

await call_tool("create_collection", {"collection_name": "MyCollection"})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collection_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

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

Annotations provide only that the tool is not read-only, not idempotent, and not destructive. The description adds the return format and an example but does not disclose side effects, error handling (e.g., duplicate collection names), or any prerequisites/permissions. This leaves significant behavioral ambiguity.

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 appropriately concise, leading with the primary purpose, followed by a clearly structured return format section and a practical example. Every section earns its place with no redundancy or unnecessary verbosity.

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

Completeness3/5

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

For a simple one-parameter tool, the description covers the basic operation and return format. However, it lacks context about what a collection is in the surrounding domain (Blender), what happens on failure, and how this fits into the broader workflow. The output schema helps but the description remains incomplete for fully autonomous selection.

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 coverage is 0%, so the description must compensate for explaining the parameter. It only offers an example value ('MyCollection') without describing naming rules, length limits, or uniqueness requirements. This adds minimal semantic value beyond the raw 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?

The description clearly states the action: 'Create a new collection.' This is a specific verb-resource pair that distinguishes the tool from related siblings like add_to_collection, which implies adding to an existing collection rather than creating a new one.

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 a new collection is needed, but it does not explicitly state when to use this tool versus alternatives such as add_to_collection. No when-not-to-use or exclusion conditions are provided, so the guidance remains implicit and minimal.

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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