video-to-srt

Generate timecoded SRT subtitles from local video or audio files. Use when a user wants a local low-cost subtitle workflow, asks to transcribe local media in...

This skill appears to do what it says: it runs a local Python transcription tool (faster-whisper) inside a venv and writes an SRT next to the input. Before installing or running it, consider: 1) It will pip-install faster-whisper (third-party code) into a local virtualenv — review and permit package installation. 2) The model weights will likely be downloaded from the Hugging Face Hub (network traffic and potentially many gigabytes of storage) unless you already have cached models — be prepared for bandwidth and disk usage and confirm you want that. 3) Ensure your environment has python3 (and typically an ffmpeg binary or equivalent media backend) even though the registry metadata didn't declare required binaries. 4) The skill operates on local files: confirm the agent/session has permission to read the media you plan to transcribe. 5) The default language is Chinese (zh); change to --language auto or set the language explicitly if that is not desired. If these points are acceptable, the skill is coherent and reasonable for local transcription.

Type: OpenClaw Skill Name: video-to-srt Version: 1.0.0 The skill provides a legitimate utility for transcribing local media files into SRT subtitles using the faster-whisper library. The implementation includes a setup script (run_local_subtitles.sh) that correctly isolates dependencies and model caches within the skill's directory, and the Python logic (transcribe_to_srt.py) is focused entirely on media processing without any signs of data exfiltration, malicious execution, or prompt injection.