lovart-skill: A skill for lovart agent

by lovartai · Codex Skill · ★ 142

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

How to install lovart-skill

npx skills add lovartai/lovart-skill

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

Security audit verdict: SAFE · quality 65/100

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.

agentlovartopenclawskill

Quick Facts

Stars142
Forks18
LanguagePython
CategoryCodex Skill
Quality Score65/100
Open Issues2
Last Updated2026-10-22
Created2026-04-09
Platformspython
Est. Tokens~15k

About lovart-skill

lovart-skill English 日本語 AI Agent Skills for Lovart — generate images, videos, and audio from your AI coding assistant. ✨ What it does This skill connects OpenClaw (and other AI coding assistants) to Lovart's Agent OpenAPI, enabling: 🖼️ Image generation — posters, logos, illustrations, banners, mockups, etc.

Compatible Skills

These tools work well together with lovart-skill for enhanced workflows:

  • Agentic-SEO-Skill — semantic(0.20)+complementary+same_lang+similar_pop+shared_platform (57%)
  • paper-fetch — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (57%)
  • claude-code-cost-estimate — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (56%)
  • fireworks-skill-memory — semantic(0.15)+complementary+same_lang+similar_pop+shared_platform (55%)

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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