novella: MangaV - 端到端 AI 漫剧创作平台。集成 13 大 AI 大模型、视听多模态与 FFmpeg 硬件加速引擎,输入一本小说

by Agions · Agent Tool · ★ 128

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

How to install novella

git clone https://github.com/Agions/novella.git

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

Security audit verdict: SAFE · quality 51/100

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.

aiai-mangaai-toolsanime-generatorcomputer-visioncyberpunkdeepseekffmpegllmmanga

Quick Facts

Stars128
Forks29
LanguageTypeScript
CategoryAgent Tool
LicenseMIT
Quality Score51/100
Last Updated2026-09-08
Created2026-02-14
Platformsnode
Est. Tokens~13k

About novella

Novella (Novella AI) · Studio v0.0.1 (Multi-Agent Edition) 输入剧本、小说或 AI 提示词,Multi-Agent 智能体集群自动协同精织为 4K 原生视听漫剧 —— 基于 Tauri v2 + React 19 + Rust Engine 的端到端开源桌面应用体系。 📖 在线文档 · 📥 下载桌面端 · 🐛 报告问题 📖 简介 (Overview) Novella (Novella AI)

Compatible Skills

These tools work well together with novella for enhanced workflows:

  • Nomi — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (69%)
  • clipforge — semantic(0.38)+complementary+rare_topics+same_lang+similar_pop+shared_platform (68%)
  • Orkas-VideoStudio — semantic(0.38)+complementary+rare_topics+same_lang+similar_pop+shared_platform (68%)
  • vibeframe — semantic(0.36)+complementary+rare_topics+same_lang+similar_pop+shared_platform (67%)
  • awesome-grok-imagine-prompts — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)

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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 Agent Tool tools