Overview
Academic Research Skills (ARS) is a professional academic research toolkit for Claude Code, packaging the complete research workflow into orchestratable AI skill pipelines.
A “tool for tools” — helping AI better assist researchers, not replace them.
Four Skill Packages
Deep Research — 13 specialized agents, 7 working modes
| Mode | Purpose |
|---|---|
| Full Research | End-to-end academic study |
| Quick Brief | Rapid literature overview |
| Lit Review | Systematic literature review |
| Systematic Review | PRISMA protocol + meta-analysis |
| Fact Check | Claim accuracy verification |
Academic Paper — 12 agents, 10 modes
APA 7.0 IEEE MLA Chicago Vancouver
Academic Paper Reviewer
5 independent reviewers simulating EIC + 3 peer reviewers + Devil’s Advocate with 0-100 scoring rubric.
Academic Pipeline
10-stage workflow: Research → Write → Integrity Check → Review → Revise → Re-review → Re-revise → Final Check → Finalize. Each stage has a mandatory quality gate.
Key Innovations
- Anti-Hallucination Verification — mandatory claim-to-source cross-checking
- Style Calibration — automatic adaptation to target journal style
- Socratic Mentoring — guides researchers through questions
Tech Stack
Python LaTeX Pandoc YAML GitHub Actions
Why This Matters
Academic writing demands extreme rigor, and AI hallucination is the biggest obstacle. ARS fights hallucination with process and verification.