Openclaw Mlx Audio

Local TTS/STT integration for OpenClaw using mlx-audio - Zero API keys, Zero cloud dependency

What to consider before installing: - Verify the upstream source: SKILL.md and docs reference a GitHub repo; confirm the repository (and commit history) before running install.sh. The registry record lacks a homepage, so validate the source yourself. - Inspect install.sh and the external installer URLs (astral.sh and uv tool) before running. The installer uses curl | sh and uv tool install to fetch mlx-audio binaries — this will download and execute code from the network. If you are uncomfortable, download the repo and examine artifacts offline or run install in a sandbox/VM. - Decide whether you need the Python servers. The package claims CLI-only in some places but includes python-runtime/*.py (HTTP endpoints that accept uploads). If you want minimal attack surface, disable or avoid starting the Python servers and use the CLI-only paths. - Check what environment variables your agent exposes. The plugin spawns child processes that inherit process.env; any sensitive env values accessible to the agent could be seen by the invoked CLI tools. Remove or isolate secrets where possible before running. - Run the tests locally in a controlled environment (bash test/run_tests.sh) to verify behavior. Prefer manual verification of mlx_audio CLI commands (which the plugin will call) before integrating into your main OpenClaw instance. - If you require higher assurance, ask the maintainer for an authoritative repo URL and a signed release or for an explanation of why Python servers are present despite CLI-only claims. That will raise confidence and resolve the architectural inconsistency. Additional info that would raise confidence: a public GitHub repo with release tags, commit history, and community reviews; an install path that avoids curl|sh (or a documented, auditable release tarball); clarification whether python-runtime servers are optional and how to disable them.

Type: OpenClaw Skill Name: openclaw-mlx-audio Version: 0.2.1 The skill bundle provides local Text-to-Speech (TTS) and Speech-to-Text (STT) integration for Apple Silicon devices using the mlx-audio framework. The core logic in `src/index.ts` and the Python servers in `python-runtime/` safely use command-line interface (CLI) calls via `spawn` and `subprocess.run` to perform audio processing. While the bundle contains an unusually large amount of documentation and scripts related to an 'autoresearch' or 'auto-improve' workflow (e.g., `scripts/auto-improve.sh`, `AUTORESEARCH_PLAN.md`), these appear to be artifacts of an AI-assisted development process aimed at improving code quality and success rates rather than malicious prompt injection. No evidence of data exfiltration, unauthorized persistence, or intentional backdoors was found.