Set origins for multiple objects in one call by specifying each object's name and origin type. Eliminate repetitive per-object origin adjustments in Blender.
Set origins for multiple objects in one call.
Each entry: {"name": "Obj", "origin_type": "GEOMETRY"}
Args: origins: List of origin dicts.
| Name | Required | Description | Default |
|---|---|---|---|
| origins | Yes |
Changes observed during successful MCP inspections.
v3.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full behavioral disclosure. It states it 'sets origins' but does not explain what an origin is, whether it modifies geometry or transform, whether it is reversible, or any side effects. As a mutation tool, it lacks critical behavioral context like irreversibility or required selection state.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear first sentence stating the purpose, followed by an example and parameter explanation. It is front-loaded and avoids fluff. However, the example could be more explanatory but is still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a batch operation with a nested object structure and no output schema, the description is incomplete. It does not explain allowed values for 'origin_type', whether 'name' refers to an object name or identifier, or any constraints on the list. There is no guidance on error handling or return behavior, leaving an agent without enough detail to reliably construct a valid call.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 provides an example entry '{"name": "Obj", "origin_type": "GEOMETRY"}' and explains the parameter is a list of origin dicts. This adds meaning about the expected structure (keys 'name' and 'origin_type') but does not enumerate possible values for 'origin_type' or clarify the 'name' field, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Set origins for multiple objects in one call' which clearly identifies the action (setting origins) and the scope (multiple objects, batched). It distinguishes itself from the sibling tool 'set_origin' by explicitly mentioning 'multiple objects in one call', so an agent can tell them apart without opening schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for batching multiple objects but does not explicitly state when to prefer this over the singular 'set_origin' or when not to use it. There is no mention of alternatives or exclusion criteria, only the phrase 'multiple objects in one call' which serves as a weak usage signal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.