by alfonso0512 · Codex Skill · ★ 366
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🎓 AI 科研论文写作助手 - 30 个 Prompt 模板覆盖论文写作全流程。支持中英文翻译、润色、文献综述、投稿回复、基金申请等。
| Stars | 366 |
| Forks | 31 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 59.3204802025043/100 |
| Open Issues | 1 |
| Last Updated | 2026-07-15 |
| Created | 2026-03-18 |
| Platforms | python |
| Est. Tokens | ~6k |
These tools work well together with research-writing-skill for enhanced workflows:
Looking for a research-writing-skill alternative? If you're comparing research-writing-skill with other codex skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
说人话｜中文优先的去 AI 味改写 skill：保事实、分场景、改完可直接发。Chinese-first rewrite skill for Codex / Claude Code / Cursor / ChatGPT
📚 Real-world OpenClaw automation examples from Moltbook
🔬🦞 A self-evolving AI research colleague for scientists. 285 skills, zero hallucination, persistent memory.
Strip AI-writing tells from papers and grant proposals (NSF/NIH), while keeping scholarly voice and tying clai
An AI workflow skill pack for research, competitions, and innovation projects.
AI writing skill that eliminates detectable AI patterns. Works with Claude Code, Codex, Cursor, Gemini CLI, an
Explore other popular codex skill tools:
research-writing-skill is 🎓 AI 科研论文写作助手 - 30 个 Prompt 模板覆盖论文写作全流程。支持中英文翻译、润色、文献综述、投稿回复、基金申请等。. It is categorized as a Codex Skill with 366 GitHub stars.
research-writing-skill is primarily written in Python. It covers topics such as academic-writing, ai-writing, openclaw.
You can find installation instructions and usage details in the research-writing-skill GitHub repository at github.com/alfonso0512/research-writing-skill. The project has 366 stars and 31 forks, indicating an active community.
research-writing-skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to research-writing-skill on Agent Skills Hub include shuorenhua, awesome-openclaw-usecases-moltbook, ScienceClaw. 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: