TG Voice Whisper Transcriber

Automation skill for TG Voice Whisper Transcriber.

This skill is coherent with its stated purpose but has several concerning/ambiguous bits you should resolve before installing: 1) Fix the command placeholders — the SKILL.md uses 'PATH' literally; ensure file path substitution is safe (e.g., use "$FILEPATH"). 2) Correct the cleanup command — 'rm PATH /tmp/whisper/*' looks wrong and may not delete the intended file(s); use 'rm "$FILEPATH" /tmp/whisper/*' or explicit paths. 3) Reconsider '--break-system-packages' in pip install; prefer a virtualenv/container to avoid damaging system Python packages. 4) Expect large Python dependencies (torch) and model downloads during first run despite the 'offline after install' claim; ensure network access and disk are acceptable. 5) The skill proposes spawning persistent background sessions/cron jobs every 5s — verify you want continuous background processing and reduce frequency if needed. 6) Run this in a sandboxed environment (container or VM) if you are not comfortable with pip/system changes or persistent background agents. If the author can provide corrected example commands, a safer install path (virtualenv), and an explanation for the --break-system-packages flag, confidence would increase.

Type: OpenClaw Skill Name: tg-voice-whisper Version: 1.0.0 The skill bundle is benign. It uses standard tools (`ffmpeg`, `openai-whisper`) to transcribe audio files locally and replies with the transcription, then deletes the files for privacy. All operations are confined to the agent's expected directories (`/root/.openclaw/media/inbound/`, `/tmp`) and do not involve external network calls, credential access, or system-level persistence mechanisms. The instructions for the agent are clear and align with the stated purpose, showing no evidence of prompt injection for malicious intent.