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S2 Spatial Element Layer & 4D Semantic Tensor Map
作者
MilesXiang
· GitHub ↗
· v1.0.0
· MIT-0
119
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当前安装
1
版本数
在 OpenClaw 中安装
/install s2-sel-4d-semantic-tensor-map
功能描述
S2 Spatial Element Layer & 4D Semantic Tensor Map. Integrates L0-L4 layer architecture, 20 material physics tensors, and Chronos backward-persistence time-sl...
安全使用建议
This package appears coherent and local-only, but review these operational points before installing: 1) Validate in simulation — the code enforces sensor-fusion rules (e.g., disabling visual depth for clear_glass) which can affect robot safety; test thoroughly on hardware. 2) Confirm there are no hidden network calls in your runtime environment (the included files do not call external endpoints). 3) Check the legal/operational claim about '60s backward-persistence' to ensure it aligns with your policy and liability model before you rely on it for safety-critical decisions. 4) Review the S2-CLA license restrictions if you plan to redistribute or integrate the skill into commercial bundles.
功能分析
Type: OpenClaw Skill
Name: s2-sel-4d-semantic-tensor-map
Version: 1.0.0
The skill bundle provides a specialized framework for spatial navigation and material analysis in robotics (S2-SEL). The Python code in core/s2_geojson_parser.py is a standard parser for GeoJSON data, and the instructions in SKILL.md and data/s2_material_tensor_library.json are strictly aligned with the stated purpose of guiding an agent through physical environments based on material properties. No indicators of data exfiltration, malicious execution, or harmful prompt injection were identified.
能力标签
能力评估
Purpose & Capability
Name/description match the included artifacts: a parser (core/s2_geojson_parser.py), a local material tensor library, examples, and documentation. All requested resources are local files; nothing unrelated (e.g., cloud credentials or unrelated binaries) is required.
Instruction Scope
SKILL.md prescribes strict runtime behavior (e.g., always retrieve tensors from s2_material_tensor_library and disable visual depth for clear_glass). These directives operate only on the provided local files and S2-GeoJSON inputs, but they are prescriptive about sensor fusion choices (which has operational/safety implications). The skill does not instruct reading unrelated system files, environment variables, or sending data externally.
Install Mechanism
Instruction-only skill with one small Python file and local JSON assets; no install spec, no network downloads, no package manager actions. Low install risk.
Credentials
No environment variables, credentials, or config paths are required. All necessary data is bundled with the skill (material tensor JSON, examples).
Persistence & Privilege
Skill is not marked always:true and does not request persistent system privileges or modify other skills. It can be invoked by the agent normally; autonomous invocation is platform default and not a concern here.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install s2-sel-4d-semantic-tensor-map - 安装完成后，直接呼叫该 Skill 的名称或使用
/s2-sel-4d-semantic-tensor-map触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
## [1.0.0] - 2026-04-07
### 🏗️ 架构升级
- **SSSU 图层化重构**：确立 L0 至 L4 五层空间要素叠合架构，实现建筑设计与机器人导航的语义对齐。
- **4D Chronos 注入**：正式将“时间切片”引入空间要素参数项。支持 `DEFAULT` 泛时态与“精确到秒”的动态切片。
### ✨ 新增功能
- **物理张量库 (L3)**：发布包含玻璃、地毯、大理石等 20 种材质的物理张量代码表，支持视觉/雷达权重动态调整。
- **逆向持存验证**：实装“60秒逆向持存”逻辑，确认 T 时刻的状态代表 T-60s 区间的物理一致性。
- **S2-GeoJSON 标准**：发布基于 GeoJSON 扩展的 `.geojson` 交换格式，支持 `properties.tensors` 嵌套结构。
### 🔧 核心组件
- **解析引擎发布**：提供 Python 版 `s2_geojson_parser.py`，实现从地图要素到机器人行为干预指令的自动化转换。
*桃花源世界模型（S2-SWM）开源社区 持续驱动*
元数据
常见问题
S2 Spatial Element Layer & 4D Semantic Tensor Map 是什么？
S2 Spatial Element Layer & 4D Semantic Tensor Map. Integrates L0-L4 layer architecture, 20 material physics tensors, and Chronos backward-persistence time-sl... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 119 次。
如何安装 S2 Spatial Element Layer & 4D Semantic Tensor Map？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install s2-sel-4d-semantic-tensor-map」即可一键安装，无需额外配置。
S2 Spatial Element Layer & 4D Semantic Tensor Map 是免费的吗？
是的，S2 Spatial Element Layer & 4D Semantic Tensor Map 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
S2 Spatial Element Layer & 4D Semantic Tensor Map 支持哪些平台？
S2 Spatial Element Layer & 4D Semantic Tensor Map 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 S2 Spatial Element Layer & 4D Semantic Tensor Map？
由 MilesXiang（@spacesq）开发并维护，当前版本 v1.0.0。
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