VideoHub: 一个集成 AI 转写与配音功能的多平台视频处理工具，支持 YouTube、TikTok/抖音、Instagram、Bilibili 和 Twitter/X

Last updated: 2026-07-23 · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: CAUTION · quality 58/100

Flagged: sudo usage. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

Quick Facts

Stars	97
Forks	16
Language	Python
Category	Codex Skill
License	MIT
Quality Score	58/100
Open Issues	3
Last Updated	2026-07-23
Created	2025-09-24
Platforms	browser, codex, python
Est. Tokens	~15k

About VideoHub

视频转录工具 (Video Hub) 当前版本: v0.1.4 简体中文 | English 这是一个功能强大的桌面应用程序，使用 PyQt6 构建现代化图形界面，支持 YouTube、Twitter/X、抖音/TikTok、Instagram、Bilibili、寇享/koushare 等多平台视频内容的智能处理。提供媒体导入与处理、语音转录、双语字幕生成、AI 配音、内容摘要等完整工作流，并配备闲时调度、批量处理、Claude Code Skills 等高级功能。 ✨ 加入讨论群 ✨ 核心功能 🎬 多平台视频处理 🎥 平台支持: YouTube、Twitter/X、抖音、Bilibili 、寇享/koushare等主流视频平台智能处理: 支持视频/音频导入与本地处理，可选择完整视频或仅音频模式精准转录: 基于 OpenAI Whisper 的高质量语音转录技术多格式字幕:...

Compatible Skills

These tools work well together with VideoHub for enhanced workflows:

python-mcp-server-client — semantic(0.17)+complementary+shared_fw(openai)+same_lang+similar_pop+shared_platform (59%)
union-search-skill — semantic(0.36)+complementary+same_lang+similar_pop+shared_platform (58%)
Document-illustrator-skill — semantic(0.35)+complementary+same_lang+similar_pop+shared_platform (57%)
mcp-youtube-transcript — semantic(0.16)+complementary+same_lang+similar_pop+shared_platform (56%)

VideoHub alternative? Top 1 similar tools

Looking for a VideoHub alternative? If you're comparing VideoHub with other codex skill tools, these 1 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

theorist by blader · ⭐ 191
A Codex/Claude skill that maintains per-repo operating theory documents.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

View on GitHub → Browse Codex Skill tools