skills: Agent skill library for PixVerse CLI — helps AI agents generate videos and images through structured

by PixVerseAI · Codex Skill · ★ 62

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

Security audit verdict: SAFE · quality 69/100

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.

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

Stars62
Forks5
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score69/100
Open Issues1
Last Updated2026-10-29
Created2026-03-05
Platformsclaude-code, cli, codex, python
Est. Tokens~15k

About skills

PixVerse Skills Agent skill library for PixVerse CLI — helps AI agents (Claude Code, Cursor, Codex, etc.) generate videos and images through structured, composable workflows. What is this? PixVerse CLI is a UI-free version of pixverse.ai — all models, parameters, and capabilities from the website are available as CLI commands with structured JSON output.

Compatible Skills

These tools work well together with skills for enhanced workflows:

  • rg_history — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (52%)

skills alternative? Top 2 similar tools

Looking for a skills alternative? If you're comparing skills with other codex skill tools, these 2 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • schematic by blader · ⭐ 238

    Claude Code / Codex skill: reverse engineer a product & technical spec from a git branch

  • 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:

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