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overte_entity_spawn

Spawns virtual objects or 3D models in Overte at specified coordinates, with configurable type, scale, position, and optional script attachment.

Instructions

Spawn a virtual object or 3D GLB model in-world at the specified coordinates.

Live when scripts/overte-mcp-bridge.js is connected to the FastAPI WS hub; otherwise returns a clearly labeled simulated confirmation.

Return Format

{"success": bool, "message": str, "data": {"source": str, "entity": {...}}}

Examples

overte_entity_spawn(name="MyBox") overte_entity_spawn(name="Tree", entity_type="Model", model_url="https://example.com/tree.glb", position=[10, 0, -5])

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ctxNo
nameYesName of the entity to spawn.
typeNoEntity type: Box, Sphere, Web, or Model.Box
scaleNoX, Y, Z dimensions.
positionNoX, Y, Z translation coordinates.
model_urlNoGLB/FBX model resource URL if type is Model.
permanentNoIf True, entity persists across domain-server restarts (lifetime=-1).
script_urlNoOptional JavaScript behavior script URL to attach.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly discloses the live-versus-simulated behavior and the exact return format, which is critical for the agent to interpret results correctly. It stops short of discussing permissions or reversibility, but for a spawn operation this is adequate.

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 well-structured with a clear opening statement, a note on live/simulated mode, a return format section, and examples. Every section earns its place without unnecessary fluff, making it easy to scan and understand quickly.

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 the tool has 8 parameters and no annotations, the description provides essential context: purpose, simulation behavior, and return shape. The examples and return format compensate for a lack of behavior details like coordinate units or persistence. It is not exhaustive but is complete enough for the agent to invoke correctly.

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 88%, so the baseline is 3. The description adds value through examples that illustrate parameter combinations, such as using 'entity_type="Model"' with 'model_url', and 'position' as a coordinate array. This goes beyond simply restating schema fields, though it does not clarify the undocumented 'ctx' parameter.

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 'Spawn a virtual object or 3D GLB model in-world at the specified coordinates,' using a specific verb and resource. This distinguishes it from sibling tools like overte_script_inject, overte_sampling_assist, and overte_domain_status, which serve entirely different purposes.

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

Usage Guidelines4/5

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

The description provides practical usage context by noting that it is live when the bridge is connected and otherwise returns a simulated confirmation. It also gives examples of typical calls. However, it does not explicitly mention alternatives or when not to use it, though the sibling context makes the differentiation clear.

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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