scientific-agent-skills: Turn any AI agent into an AI Scientist

How to install scientific-agent-skills

npx skills add K-Dense-AI/scientific-agent-skills
git clone https://github.com/K-Dense-AI/scientific-agent-skills.git ~/.agents/skills/scientific-agent-skills   # user-level

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 46/100

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.

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.

Quick Facts

About scientific-agent-skills

Scientific Agent Skills [](https://www.youtube.com/@K-Dense-

Compatible Skills

These tools work well together with scientific-agent-skills for enhanced workflows:

• scientific-agent-skills — semantic(0.83)+complementary+same_lang+shared_platform (65%)
• ai-agent-skill-for-video-workflow — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (60%)
• SciAgent-Skills — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (60%)
• agent-skills — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (60%)

scientific-agent-skills alternative? Top 2 similar tools

Looking for a scientific-agent-skills alternative? If you're comparing scientific-agent-skills with other codex skill tools, these 2 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

• schematic by blader · ⭐ 238

  Claude Code / Codex skill: reverse engineer a product & technical spec from a git branch

• theorist by blader · ⭐ 191

  A Codex/Claude skill that maintains per-repo operating theory documents.

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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:

• SlowMist agent-security taxonomy
• Liu et al., An Empirical Study of Agent Skill Security (2026)
• Our census dataset (DOI 10.5281/zenodo.21292799) · Hugging Face mirror
• How we grade: all 42 rules, the source tiers and known limits
• Full methodology & who runs this