Short Video Parser

此技能用于解析短视频链接，支持解析抖音、快手、B站等多个主流平台的短视频和图文链接，并能自动提取语音内容转录为文字。适用于需要批量获取视频元数据或将视频内容转为文本的场景时使用此 skill。

This package implements exactly the parsing and transcription behavior it advertises, but the registry metadata is incomplete and there are privacy implications you should consider before installing: - The transcribe flow uploads extracted audio to SiliconFlow (Bearer token from .env or --api_key). If you provide that API key the skill will send your audio to a third‑party service. If you don't want audio uploaded, do not provide the API key or avoid running the transcription step. - SKILL.md and scripts require ffmpeg on PATH (used via subprocess). The registry does not declare this requirement — install ffmpeg if you plan to transcribe. - The code downloads videos and stores them in tmp/ and writes Markdown reports to demos/. If you enable auto_cleanup=false or omit cleanup, media files are retained on disk. - The optional parse_api_url allows using an external parsing API; setting it causes your share URLs to be sent to that endpoint — only set it to a URL you trust. - Packaging mismatch: registry metadata not declaring required env vars/binaries is a red flag (sloppy or incomplete packaging). Prefer to inspect/run the code in a sandbox or VM first. Review .env and scripts/transcribe.py to confirm endpoints and remove or replace the external transcription endpoint if needed. Recommended actions before use: inspect the code locally, run in an isolated environment, avoid supplying API keys you don't trust, and consider building a local/no‑upload transcription path if you need to protect sensitive content.

Type: OpenClaw Skill Name: yby6-video-parser-skill Version: 2.0.0 The skill bundle is a comprehensive video parsing and transcription tool supporting over 20 platforms, including Douyin, Bilibili, and Twitter. It extracts video metadata and utilizes ffmpeg via the subprocess module to extract audio for transcription through the SiliconFlow API. The code logic, including the platform-specific scrapers in the scripts/parser/ directory and the transcription workflow in scripts/transcribe.py, is consistent with the stated purpose. While it performs network requests and local file operations, there is no evidence of malicious intent, data exfiltration, or unauthorized command execution.