awesome-research-skills: Open-source Agent Skills for planning, drafting, revising, and polishing SCI/SSCI papers—while preserving

by Yila-AI · Codex Skill · ★ 138

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

How to install awesome-research-skills

npx skills add Yila-AI/awesome-research-skills --global --agent codex --skill '*' --yes --copy
npx skills add Yila-AI/awesome-research-skills --global --agent codex --skill science-research-writing --yes --copy

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

Security audit verdict: SAFE · quality 67/100

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.

academic-writingagent-skillsai-researchclaude-codecodexmanuscript-writingopenclawprompt-engineeringresearch-writingsci

Quick Facts

Stars138
Forks15
LanguagePython
CategoryCodex Skill
LicenseApache-2.0
Quality Score67/100
Open Issues1
Last Updated2026-10-21
Created2026-07-17
Platformsclaude-code, codex, python
Est. Tokens~19k

About awesome-research-skills

Awesome Research Skills The research workflow every AI agent should have. A growing open-source Skill stack for the full research lifecycle—from discovering and understanding papers to writing, reviewing, polishing, and presenting research. Available today: research writing, faithful academic polishing, academic de-templating, and paper-to-slides. More stages are being built.

Compatible Skills

These tools work well together with awesome-research-skills for enhanced workflows:

  • AlterLab-Academic-Skills — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
  • writing-agent — semantic(0.40)+complementary+same_lang+similar_pop+shared_platform (64%)
  • academic-paper-writer — semantic(0.39)+complementary+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 Codex Skill tools