by blixvip · Claude Skill · ★ 169
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
git clone https://github.com/blixvip/easyedit && cd easyedit
Taken from the project's README on GitHub.
None of the 43 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 43 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
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.
| Stars | 169 |
| Forks | 26 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 68/100 |
| Open Issues | 26 |
| Last Updated | 2026-11-07 |
| Created | 2026-09-16 |
| Platforms | claude-code, python |
| Est. Tokens | ~16k |
Type a movie. Get a captioned speech + beat-cut fan edit. Local-first · no API keys · works with your AI bot Type a movie name and get a finished fan edit. It makes the kind that's all over social media: the film's best speech with animated word-by-word captions, then a fast montage cut to the beat of a song. The finished video is saved to as 1920×1080 at 60fps.
These tools work well together with easyedit for enhanced workflows:
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Raw talking-head take in, finished reel out. Open-source AI video editor for Claude Code.
Guardrailed video editing MCP server for AI agents. FFmpeg, Hyperframes, repurposing tools, Python client, and
Guardrailed video editing MCP server for AI agents. FFmpeg, Hyperframes, repurposing tools, Python client, and
AI 自動剪輯工作區:放好素材,用白話文跟 Claude Code、Codex、MiniMax Code、Cursor 說「剪乾淨」「做成片」,自動剪 NG、照講稿上字幕、加資訊卡與情境動畫、配音效。Open-sourc
Turn your coding agent into a video studio: describe a video in plain language, and your agent writes the time
A local video studio for your coding agent. Describe a video in one sentence: your agent directs, your machine
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 43 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: