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The 4D Acoustic Engine

by MilesXiang · GitHub ↗ · v1.4.0 · MIT-0
cross-platform ⚠ suspicious
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Install in OpenClaw
/install s2-voice-multimodal-aligner
Description
Analyzes acoustic emotion and semantic intent to trigger a timed, multimodal sequence of smart home actions for context-aware environment control.
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install s2-voice-multimodal-aligner
  3. After installation, invoke the skill by name or use /s2-voice-multimodal-aligner
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Slug s2-voice-multimodal-aligner
Version 1.4.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 5
Frequently Asked Questions

What is The 4D Acoustic Engine?

Analyzes acoustic emotion and semantic intent to trigger a timed, multimodal sequence of smart home actions for context-aware environment control. It is an AI Agent Skill for Claude Code / OpenClaw, with 137 downloads so far.

How do I install The 4D Acoustic Engine?

Run "/install s2-voice-multimodal-aligner" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is The 4D Acoustic Engine free?

Yes, The 4D Acoustic Engine is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does The 4D Acoustic Engine support?

The 4D Acoustic Engine is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created The 4D Acoustic Engine?

It is built and maintained by MilesXiang (@spacesq); the current version is v1.4.0.

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