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Cluster imported-splat objects

scene_imported_objects_run

Cluster an imported splat's geometry into labeled facts.objects, carrying provenance and confidence values to support reliable scene reasoning.

Instructions

Cluster an imported splat's geometry into facts.objects (POST /imported_objects). Labels carry geometry/synthetic-view provenance — confidence 0.0 is honest, not a bug.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scan_idYes
Install Server

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It does disclose the mutating POST operation and adds a genuinely useful caveat that 'confidence 0.0 is honest, not a bug,' plus provenance semantics. However, it does not mention side effects, rerun behavior, or whether the operation is asynchronous.

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 two sentences with no filler. The core action is front-loaded, and the second sentence adds a valuable clarification about label provenance and confidence scores that would otherwise be surprising.

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 one-parameter tool, the description covers the action, the endpoint, and an important output semantic. However, with no output schema and no annotations, it still omits what the response looks like, whether the run is asynchronous, and what prerequisites must be satisfied before calling it.

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?

The input schema contains only scan_id with no description, and schema description coverage is 0%. The description never explains what scan_id should refer to or how to obtain it, so the parameter meaning is left entirely to its self-descriptive name. That prevents a score of 1 but does not compensate for the documentation gap.

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 opens with a specific action verb ('Cluster') and names the target resource ('an imported splat's geometry into facts.objects'), while also giving the exact endpoint. It is clear what the tool does, though it does not explicitly differentiate itself from the sibling scene_imported_objects.

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 guidance is given about when to use this tool versus alternatives such as scene_imported_objects or scene_synthetic_views. There are no prerequisites, no mention of checking job status afterward, and no when-not-to-use conditions; the context is only weakly implied by 'an imported splat's geometry'.

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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