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The 4D Acoustic Engine
作者
MilesXiang
· GitHub ↗
· v1.4.0
· MIT-0
137
总下载
0
收藏
0
当前安装
5
版本数
在 OpenClaw 中安装
/install s2-voice-multimodal-aligner
功能描述
Analyzes acoustic emotion and semantic intent to trigger a timed, multimodal sequence of smart home actions for context-aware environment control.
安全使用建议
This skill appears to be what it says: it simulates audio analysis and — only if you explicitly enable real actuation and provide a Home Assistant token — will it POST commands to your local Home Assistant. Before enabling real actuation: (1) keep S2_ENABLE_REAL_ACTUATION=False during review and testing; (2) inspect the code (you already have it) and run in an isolated environment; (3) if you need real actuation, provide HA_BASE_URL pointing to an internal IP/hostname and a short-lived or scoped token, not a highly privileged global credential; (4) note the SKILL.md -> env filename mismatch (.env.example vs env_template.txt) and correct it before following the copy/edit step; (5) consider network controls or firewall rules that prevent the skill from reaching unintended hosts (and verify SSRF protections against IPv6/DNS edge-cases). If you are not comfortable storing a Home Assistant token on the host, do not enable real actuation.
功能分析
Package: s2-voice-multimodal-aligner (xpi)
Version: 1.4.0
Description:
The package is a voice-controlled smart home integration tool designed for Home Assistant. It demonstrates high security standards, including explicit SSRF protection (validating that target URLs resolve to private/loopback IP addresses), environment variable management using python-dotenv with safe fallbacks, and a 'Dry-Run' mode to prevent accidental physical actuation. No malicious code, unauthorized shell execution, or secret exfiltration logic was detected.
能力评估
Purpose & Capability
Name/description (acoustic emotion → smart-home actions) match the included code: numpy/scipy for DSP, a small alignment engine, and POSTs to a Home Assistant-style REST API. Declared dependencies (numpy, scipy, requests, python-dotenv) are appropriate for the stated functionality.
Instruction Scope
SKILL.md instructs standard setup (pip install -r requirements.txt, copy an env template, run python skill.py). The runtime instructions and code do what they describe: simulate audio, infer an intent, and optionally POST to HA. Minor inconsistencies: SKILL.md refers to '.env.example' while the repo contains env_template.txt (filename mismatch). The skill does not read arbitrary user files or secrets beyond the Home Assistant token and .env, and audio input is simulated (no microphone capture).
Install Mechanism
No install spec; installation relies on pip with a pinned requirements.txt (standard PyPI packages). That is a normal, traceable install path and does not use ad-hoc downloads or unknown URLs.
Credentials
The only sensitive environment variables described (HA_BEARER_TOKEN, HA_BASE_URL, S2_ENABLE_REAL_ACTUATION) are relevant to the declared purpose. The code uses a sandbox default token and dry-run by default, which is good. However, enabling real actuation requires providing a long-lived Home Assistant token and network access to local devices — this is sensitive and should be given only to trusted runs. The SSRF protection uses socket.gethostbyname and checks is_private/is_loopback; this is appropriate but has edge cases (IPv6, DNS manipulations, or complex name resolution behaviors) that reviewers should consider.
Persistence & Privilege
The skill does not request always:true, does not modify other skills or system settings, and is user-invocable. It creates a local directory (s2_voice_vault) but otherwise does not request elevated privileges or persistent platform hooks.
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-voice-multimodal-aligner - 安装完成后，直接呼叫该 Skill 的名称或使用
/s2-voice-multimodal-aligner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
v1.4.0
- Added .env.example file to provide a safe template for environment configuration.
- Updated documentation to highlight full compatibility with cloud-native and container deployments.
- Improved environment variable handling with graceful fallback from system environment to .env, and secure sandbox defaults if neither is present.
- Introduced explicit runtime blocking: real actuation is prevented unless non-default secrets are set.
- Revised deployment instructions to guide secure setup and usage.
v1.3.1
- Now explicitly marks HA_BEARER_TOKEN as sensitive in manifest.json to meet enterprise registry requirements.
- Enforces strict dependency pinning (using ==) in requirements.txt and manifest.json for improved security and reproducibility.
- Documentation updates highlight secure injection of secrets and the importance of not committing .env files.
- Core multimodal alignment logic and zero-trust SSRF protection remain unchanged.
v1.3.0
Version 1.2.1 Changelog:
- No file changes detected; internal version bump only.
- No new features, bug fixes, or documentation updates included in this release.
v1.2.0
**Major update focused on enterprise security and compliance:**
- Introduced strict zero-trust, privacy-first architecture with enforced DevSecOps policies.
- Sensitive credentials are now required in a local `.env` file (never hardcoded or exported), using `python-dotenv`.
- Added SSRF protection: the SecurityEnforcer blocks all network requests to non-local subnets.
- By default, enables a secure dry-run mode—no real network or API calls without explicit user opt-in.
- Updated installation and deployment instructions to guide safe credential handling and execution.
- All logs now automatically redact sensitive tokens from output.
v1.0.0
S2-Voice-Multimodal-Aligner v1.0.0 initial release:
- Introduces a novel multimodal voice alignment engine analyzing both emotion and semantic meaning from speech.
- Operates in secure "dry-run mode" by default, simulating actions and printing Home Assistant API payloads to the console.
- Includes 4D Timeline Rendering: aligns user emotion and intent with sequenced, time-stamped actions for enhanced intelligent responses.
- Features detailed protocols for handling complex scenarios (e.g., migraine relief) by coordinating multiple smart home systems.
- Offers quickstart instructions for safe local setup and execution.
元数据
常见问题
The 4D Acoustic Engine 是什么？
Analyzes acoustic emotion and semantic intent to trigger a timed, multimodal sequence of smart home actions for context-aware environment control. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 137 次。
如何安装 The 4D Acoustic Engine？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install s2-voice-multimodal-aligner」即可一键安装，无需额外配置。
The 4D Acoustic Engine 是免费的吗？
是的，The 4D Acoustic Engine 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
The 4D Acoustic Engine 支持哪些平台？
The 4D Acoustic Engine 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 The 4D Acoustic Engine？
由 MilesXiang（@spacesq）开发并维护，当前版本 v1.4.0。
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