paint-mv-skills — security grade SAFE, quality 64/100

Security audit verdict: SAFE · quality 64/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by lintsinghua · Claude Skill · ★ 28

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

🔒 Is paint-mv-skills safe to install? View the security audit →

About paint-mv-skills

Agent skills that turn a song and its lyrics into a hand-painted watercolour music video (p5.brush + headless Chrome + ffmpeg), following PDoomVideo's pipeline

agent-skillsai-agentaigcanimationclaude-skillscreative-codingcursor-skillsffmpeggenerative-artlyrics

Quick Facts

Stars28
Forks5
LanguageJavaScript
CategoryClaude Skill
Quality Score63.711460917749/100
Last Updated2026-09-29
Created2026-09-25
Platformsbrowser, claude-code, node
Est. Tokens~14k

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Frequently Asked Questions

What is paint-mv-skills?

paint-mv-skills is Agent skills that turn a song and its lyrics into a hand-painted watercolour music video (p5.brush + headless Chrome + ffmpeg), following PDoomVideo's pipeline. It is categorized as a Claude Skill with 28 GitHub stars.

What programming language is paint-mv-skills written in?

paint-mv-skills is primarily written in JavaScript. It covers topics such as agent-skills, ai-agent, aigc.

How do I install or use paint-mv-skills?

You can find installation instructions and usage details in the paint-mv-skills GitHub repository at github.com/lintsinghua/paint-mv-skills. The project has 28 stars and 5 forks, indicating an active community.

What are the best alternatives to paint-mv-skills?

The top alternatives to paint-mv-skills on Agent Skills Hub include photo-abstract-editorial, opus-video-skills, RivalSearchMCP. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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 Claude Skill tools