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 HITSZ-DS · Agent Tool · ★ 146
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is NovelClaw safe to install? View the security audit →
NovelClaw ✨ A structured long-form fiction workspace centered on chapter drafting, inspectable runs, manuscript review, and memory-aware writing control. 💡 NovelClaw is not a one-shot prompt wrapper. It turns long-form fiction work into an inspectable writing workspace with sessions, storyboards, manuscript surfaces, character and world views, and editable memory banks. 🌐 Try it online: colong-idea-studio.cloud 🚀 Start locally now: .\STARTLOCAL.bat <img
| Stars | 146 |
| Forks | 18 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 65.8010108248936/100 |
| Last Updated | 2026-03-29 |
| Created | 2026-03-07 |
| Platforms | browser, python |
| Est. Tokens | ~3623k |
These tools work well together with NovelClaw for enhanced workflows:
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NovelClaw is Dynamic-memory-first collaborative AI framework for long-form story generation, chapter planning, and coherent narrative writing. It is categorized as a Agent Tool with 146 GitHub stars.
NovelClaw is primarily written in Python. It covers topics such as agent, ai, creative-writing.
You can find installation instructions and usage details in the NovelClaw GitHub repository at github.com/HITSZ-DS/NovelClaw. The project has 146 stars and 18 forks, indicating an active community.
NovelClaw is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to NovelClaw on Agent Skills Hub include NovelClaw, aser, character-arc. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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: