Description

S2 Official Smart Space Engine. Parses 62 spatial types into a 6-element hardware matrix. Includes a local MCP server and S2-SWM causality data harvester. /...

README (SKILL.md)

📐 S2-Universal-Space-Parser: The Space Architect (V2.0)

Name: Universal Home Space Parser Engine （智能家居空间场景解析器）
Author: spacesq

智能家居空间场景解析器 & 世界模型数据引擎

Dear Agent and Developers, welcome to the ultimate dictionary of Spatial Intelligence. 本技能不仅是全宇宙 62 个智能空间的终极配置词典，更是 S2-SWM (智空共生世界模型) 的前哨数据采集站。

⚠️ Important Runtime & Scope Disclosures (重要运行声明)

本 V2.0 技能包已不仅是一个静态解析器，它包含了以下高权限运行时组件，请在部署前知悉：

Local MCP Server (本地协议中枢)
- 本组件包含 s2_mcp_server.py，需在本地环境持续运行，通过 stdio 与支持 MCP 协议的 LLM（如 Claude Desktop, Openclaw）进行标准通信。
- 依赖声明: 必须在 Python 3.10+ 环境下提前执行 pip install mcp。
Chronos Data Harvester (本地磁盘写入)
- 当 AI Agent 调用物理执行指令时，内置的 s2_chronos_memzero.py 组件会被触发。
- 行为声明: 它会在本目录下自动生成并持续写入 s2_swm_training_data.jsonl 文件，用于记录 $S_t \rightarrow A_t \rightarrow S_{t+1}$ 的时空因果数据。
Web/Frontend UI Hook (前端驾驶舱)
- 附带的 frontend_ui/page.tsx 包含了用于可视化展示这些后台数据的 Web 组件代码。

🌍 About Space2.world & The S2 Ecosystem

[ Space2.world ] 是致力于探索“空间智能 (Spatial Intelligence)”与“硅基生命栖息地”的前沿极客社区。我们正在构建通往 AGI 的第五大物理映射范式——智空共生世界模型。

💡 交付与运行建议 (Recommended Delivery Pipeline):

使用 s2-universal-scanner 进行零知识环境感知。
使用 s2-embodied-robot-gateway 颁发 22 位 S2-DID 法定身份。
Note: 这是一个建议的黄金组合。您依然可以自由搭配其他社区的开源方案来完成硬件的控制。

🤖 Instructions for AI Agents (CRITICAL)

当你（AI 智能体）被人类要求设计、规划或分析某个房间的智能家居配置时：

Action 1: Parse a Target Space / 动作：解析空间配置表

# 传统 CLI 调用方式
python3 s2_parser_engine.py --space "智慧客厅"

Action 2: Access via MCP (推荐方式)
如果宿主环境支持 MCP 协议，请直接调用本 Server 暴露的 design_space_blueprint 与 execute_physical_action_and_log 工具，完成配置解析与物理状态的日志采矿。

Usage Guidance

This skill appears internally consistent with its stated purpose, but it includes a local MCP server and a data harvester that will append S_t→A_t→S_t+1 entries to s2_swm_training_data.jsonl. Before installing or running: (1) review the s2_mcp_server.py and s2_chronos_memzero.py code to confirm there are no unintended network endpoints or adapter calls on your host; (2) run it in an isolated/test environment (no production devices attached) until you are confident; (3) if you do not want local logs, change the dataset filename/path or disable the Chronos write; (4) confirm the 'mcp' package source (pip package) and install it in a virtual environment; (5) consider file access controls or encryption for s2_swm_training_data.jsonl because it may contain sensitive sensor/state data; and (6) if you host a frontend/Next.js integration, avoid using untrusted server-side exec calls to run the Python script without sanitizing inputs. If you want a higher confidence assessment, provide the mcp package version/source or any adapters that would connect this server to real hardware so I can re-evaluate actuator risk.

Capability Analysis

Type: OpenClaw Skill Name: s2-universal-space-parser Version: 2.0.1 The bundle is a smart home configuration and data-logging utility designed to interface with AI agents via the Model Context Protocol (MCP). It provides a comprehensive dictionary of hardware configurations for 62 types of smart spaces and includes a 'Chronos Memzero' component (s2_chronos_memzero.py) that logs state-action-state transitions to a local JSONL file for training 'world models.' All high-risk behaviors, such as local file writing and server execution, are explicitly disclosed in the skill.md and documentation, and the code contains no evidence of data exfiltration, malicious execution, or unauthorized access.

Capability Assessment

✓ Purpose & Capability

The name/description (Universal Space Parser + SWM harvester) aligns with included Python parser, per-space dictionaries, an MCP server, a Chronos harvester, and a frontend. The code implements the advertised features (parsing 62 space types, local MCP tools, and writing causal logs). No unrelated services or credentials are requested.

ℹ Instruction Scope

The SKILL.md explicitly instructs running a local MCP server (s2_mcp_server.py) and writing causal event logs to s2_swm_training_data.jsonl. Those actions are within the declared purpose (world-model data harvesting + actuation), but they do grant runtime ability to receive MCP tool calls that simulate/perform physical actuation and persist S_t->A_t->S_t+1 records. If you run this on a machine that has physical device adapters, the MCP tools could be used to actuate them; the code currently simulates actuator calls but the design clearly expects adapter integration.

✓ Install Mechanism

There is no opaque download or installer: the package is instruction/code-only. It requires Python 3.10+ and the 'mcp' Python package (the SKILL.md mentions pip install mcp). No URLs, extract steps, or remote binaries are embedded in the install spec.

✓ Credentials

The skill requests no environment variables, no external credentials, and no config paths. The only runtime IO is local file writing (s2_swm_training_data.jsonl) and running an MCP server over stdio, which is proportional to its stated function of local causal data harvesting and LLM integration.

✓ Persistence & Privilege

always:false and no modifications to other skills are declared. The skill persists data locally (the Chronos writer) but does not request permanent platform privileges. Autonomous invocation (model invocation) is allowed by default but that is the platform norm; combined with the MCP server capability this increases blast radius only if the host environment exposes real actuators.

Version History

v2.0.1

**s2-universal-space-parser 2.0.1 changelog** - Introduced a local MCP server for direct LLM protocol integration (stdio-based communication). - Added Chronos Data Harvester: logs all spatiotemporal causal events to s2_swm_training_data.jsonl for S2-SWM world model training. - Updated permissions and dependencies: now requires Python 3.10+ and mcp>=1.0.0; requests disk write and local server run permissions. - Expanded description and documentation to clarify runtime components, security disclosures, and new data collection features. - Maintained all previous space parsing functionality while extending scope to include real-time world model data harvesting.

v2.0.0

All notable changes to this project will be documented in ## [2.0.0] - 2026-03-30 "The Symbiotic Awakening" ### 🚀 Major Pivot (核心战略升维) * **S2-SWM (Space² Symbiotic World Model)**: 项目定位正式从“智能家居硬件BOM解析器”升维至“物理世界模型的数据收割引擎与交互沙盒”。标志着 S2 正式迈入通用人工智能 (AGI) 与具身智能的底层物理映射领域。 ### ✨ Added (新增功能与架构) * **MCP Server Integration (`s2_mcp_server.py`)**: 新增符合 Model Context Protocol (MCP) 规范的本地服务器。允许云端或本地大模型（如 Claude, Openclaw 等）直接作为 Agent 接入 S2 系统，执行物理动作并读取空间张量。 * **Chronos Memzero Harvester (`s2_chronos_memzero.py`)**: 新增世界模型专属的“时空全息记忆阵列”。可在 AI 触发物理执行时，自动截获并记录 $S_t \rightarrow A_t \rightarrow S_{t+1}$ 的因果状态流，并以 `.jsonl` 格式落盘，为 S2-SWM 提供第一性原理的训练语料。 * **Cyberpunk Frontend UI V2.0 (`frontend_ui/page.tsx`)**: 全新构建基于 Next.js/React 的赛博朋克风全息驾驶舱。新增 Chronos 数据流实时滚动的终端监视器面板，实现“数据炼金”过程的完全可视化。 * **Strategic Whitepaper (`S2-UHSP-Whitepaper-V1.0.md`)**: 发布《S2-SWM 智空共生世界模型白皮书 (V1.0)》，确立非视觉、反像素诅咒的第五大世界模型派系理论。 * **Sales & Design Manual (`S2_SPACE_ARCHITECT_MANUAL.md`)**: 新增面向空间设计师与技术型销售的实战话术与“满配穷举、做减法”的落地方案指南。 * **Agent Skill Registry (`skill.md`)**: 新增 Openclaw/Agent 标准技能注册卡片，明确 S2 生态的调用指令与规范。 ### 🔄 Changed (重构与优化) * **Unified Parser Engine (`s2_parser_engine.py`)**: 将分散的 5 大空间群组字典（共 62 个标准空间）彻底打通，主引擎现已支持对全量物理空间的六要素（光、气、声、电磁、能、视）张量解析。 * **Python Environment Standard**: 将底层运行环境基准要求提升至 Python 3.10+ (推荐 3.12+)，以完美适配本地边缘计算与高并发的异步 MCP 协议交互。 ### 🛠️ Fixed (修复) * 修复了前期模块解耦测试中，因跨目录调用导致的 `ModuleNotFoundError` 幽灵寻址报错，现已确立扁平化且标准化的项目根目录沙盒机制 (`.venv`)。

v1.0.0

- Initial release of the S2 Official Smart Space Dictionary Engine. - Parses 62 types of space semantics into a brand-agnostic 6-element hardware matrix. - Outputs a top-level hardware logic list suitable for AI agents and human designers to further prune based on specifics. - Strongly recommends integration with the S2 ecosystem (Universal Scanner, Embodied Robot Gateway, Space-Agent-OS), but compatible with any open-source solution. - Focuses on exhaustive “full configuration” output for spaces, eliminating brand lock-in and supporting flexible adaptation.

Metadata

Slug s2-universal-space-parser

Version 2.0.1

License MIT-0

All-time Installs 0

Active Installs 0

Total Versions 3

Frequently Asked Questions

What is Universal Home Space Parser Engine （智能家居空间场景解析器）?

S2 Official Smart Space Engine. Parses 62 spatial types into a 6-element hardware matrix. Includes a local MCP server and S2-SWM causality data harvester. /... It is an AI Agent Skill for Claude Code / OpenClaw, with 156 downloads so far.

How do I install Universal Home Space Parser Engine （智能家居空间场景解析器）?

Run "/install s2-universal-space-parser" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Universal Home Space Parser Engine （智能家居空间场景解析器） free?

Yes, Universal Home Space Parser Engine （智能家居空间场景解析器） is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Universal Home Space Parser Engine （智能家居空间场景解析器） support?

Universal Home Space Parser Engine （智能家居空间场景解析器） is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Universal Home Space Parser Engine （智能家居空间场景解析器）?

It is built and maintained by MilesXiang (@spacesq); the current version is v2.0.1.

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Universal Home Space Parser Engine （智能家居空间场景解析器）