lipnardo — security grade SAFE, quality 72/100

Security audit verdict: SAFE · quality 72/100

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 AgriciDaniel · Claude Skill · ★ 22

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

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About lipnardo

HeyGen avatar video generation skill for Claude Code. Batch, templates, translation, photo avatars, TTS. Stdlib-only Python.

agent-skillsai-videoanthropicavatar-videoclaude-codeclaude-skillheygenpythontalking-headvideo-generation

Quick Facts

Stars22
Forks5
LanguagePython
CategoryClaude Skill
Quality Score71.5547615468235/100
Last Updated2026-04-18
Created2026-04-17
Platformsclaude-code, python
Est. Tokens~7k

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Frequently Asked Questions

What is lipnardo?

lipnardo is HeyGen avatar video generation skill for Claude Code. Batch, templates, translation, photo avatars, TTS. Stdlib-only Python.. It is categorized as a Claude Skill with 22 GitHub stars.

What programming language is lipnardo written in?

lipnardo is primarily written in Python. It covers topics such as agent-skills, ai-video, anthropic.

How do I install or use lipnardo?

You can find installation instructions and usage details in the lipnardo GitHub repository at github.com/AgriciDaniel/lipnardo. The project has 22 stars and 5 forks, indicating an active community.

What are the best alternatives to lipnardo?

The top alternatives to lipnardo on Agent Skills Hub include SeeCut, ComfyUI-Expert, narrator-ai-cli-skill. 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