Universal Data Model for the next generation of AI-driven smart spaces

Defines a universal 6-element spatial data model using natural language parameters for AI-driven smart space perception and control.

This skill appears to do exactly what it says: create a local JSON template for a spatial primitive. Before installing or running it: (1) Inspect skill.py yourself (it is short and readable) to confirm there are no network calls or hidden behavior — the provided copy has none. (2) Be aware it will create s2_primitive_data/primitive_6_elements_template.json in the current working directory and will overwrite an existing file with that name without prompting; run in a safe/empty folder if concerned. (3) The script blocks on an input() prompt at the end — remove or handle that if you want non-interactive execution. (4) The SKILL claims a strict privacy boundary (no camera recording) — that is a design claim in the model; confirm that any real sensors or agents you later connect to this schema actually respect that boundary. (5) There is a small metadata mismatch around the homepage; if provenance/trust matters, verify the author/homepage (space2.world) before trusting broad use. Running it in an isolated environment first is recommended if you want to be extra cautious.

Type: OpenClaw Skill Name: s2-spatial-primitive Version: 1.0.0 The skill is a template generator for a spatial data model (S2-Spatial-Primitive). The Python script (skill.py) creates a local directory and a JSON file containing a schema for environmental parameters like lighting, air quality, and energy usage. It does not perform any network operations, access sensitive system files, or contain malicious instructions; its behavior is entirely consistent with its stated purpose of providing a data structure for AI agents.