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 free-revalution · Claude Skill · ★ 110
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is AIGC-Detector-Pro safe to install? View the security audit →
AIGC-Killer-Pro 论文 AIGC 检测 / AI 降率 / 毕业论文编写 基于 Claude Code 的学术论文 AI 内容检测与改写 Skill，从 5 个维度深度分析 AI 生成特征，提供科学改写指导，并支持从模板到论文的全流程生成。 English | 简体中文 需要 Claude Code + Python 3.8+ 为什么 2026 年主流 AIGC 检测平台已全面升级，AI 内容识别准确率大幅提升。单纯同义词替换已无法通过检测——必须在语义结构层面进行重构。AIGC-Killer-Pro 利用 Claude 的深层语义理解，精准识别论文中的 AI 痕迹，提供科学的改写方案。 三大模式 AIGC 检测 从 5 个维度对论文进行深度语义分析，生成段落级检测报告，精准定位高风险内容。 在 Claude Code 中直接对话即可触发： 智能改写 基于 7 大改写技法，自动改写高风险段落并输出 .docx，保持原始格式不变。 帮我改写这篇论文降低AI率：/p
| Stars | 110 |
| Forks | 8 |
| Language | Python |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 63.4327293674964/100 |
| Open Issues | 4 |
| Last Updated | 2026-06-02 |
| Created | 2026-04-07 |
| Platforms | claude-code, python |
| Est. Tokens | ~42k |
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AIGC-Detector-Pro is AIGC 检测论文 AI 降率工具 - Claude Code Skill for academic paper AI detection and rewriting. It is categorized as a Claude Skill with 110 GitHub stars.
AIGC-Detector-Pro is primarily written in Python. It covers topics such as academic, ai-detection, aigc.
You can find installation instructions and usage details in the AIGC-Detector-Pro GitHub repository at github.com/free-revalution/AIGC-Detector-Pro. The project has 110 stars and 8 forks, indicating an active community.
AIGC-Detector-Pro is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to AIGC-Detector-Pro on Agent Skills Hub include humanize-chinese, humanize, phd-skills. 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: