VideoClaw: AI 全自动化视频生成员工 | Your First AIGC Coworker. Chat an Idea. Get a Film

by HITsz-TMG · Codex Skill · ★ 1.9k

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

Featured in: AI Video Generation & Editing: Seedance, Kling & Subtitles

How to install VideoClaw

git clone https://github.com/HITsz-TMG/VideoClaw.git
git clone https://github.com/HITsz-TMG/Video-Claw.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 51/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. 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.

agentaigcfilmmakingimage-generationmulti-agent-systemopenclawopenclaw-skillsttsvideo-generation

Quick Facts

Stars1,878
Forks277
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score51/100
Open Issues14
Last Updated2026-08-26
Created2024-08-29
Platformspython
Est. Tokens~19k

About VideoClaw

VideoClaw: AI 创意视频生成员工 简体中文 | English 直接与 OpenClaw 对话:"生成 X 的视频" → 搞定。 📺 [

Compatible Skills

These tools work well together with VideoClaw for enhanced workflows:

  • video-podcast-maker — semantic(0.30)+complementary+rare_topics+same_lang+similar_pop+shared_platform (65%)
  • OpenMontage — semantic(0.24)+complementary+rare_topics+same_lang+similar_pop+shared_platform (63%)
  • MiniMax-MCP — semantic(0.33)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)

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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