> TL;DR: An MIT-licensed set of Claude Code Skills covering the entire academic research lifecycle — 13-agent deep research → 12-agent paper writing → 7-agent peer review → a 10-stage automated pipeline. A 15,000-word paper costs only $4-6 in API costs + 2-4 hours of human collaboration.
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🔥 Why Did This Skill Set Gain 11,600 Stars in a Week?
In May 2026, academic-research-skills topped GitHub Trending (Top 10) with 20,268 total stars and 11,600 new stars in 7 days. It reflects the community's deep understanding of the Claude Code "Skill" model — the point is not to let AI do your research, but to let AI handle the mechanical work while you focus your energy on the parts that genuinely require training.
> "AI is your copilot, not the pilot."
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🧠 Core Skills Overview
1. Deep Research (v2.9.4) — A 13-Agent Research Team
| Mode | Scenario | Depth |
|------|----------|-------|
| full | Complete research | Balanced |
| quick | 30-minute rapid briefing | High fidelity |
| systematic-review | PRISMA-compliant systematic review | High fidelity |
| socratic | Guided research dialogue | Originality |
| fact-check | Fact-checking | High fidelity |
| lit-review | Literature review | High fidelity |
| review | Paper evaluation | Balanced |
Core capabilities:
- Socratic guided mode — helps you clarify vague ideas
- PRISMA systematic reviews + meta-analysis
- Intent detection — automatically identifies what you actually want to research
- Conversation health monitoring — keeps the AI on track
- Semantic Scholar API verification — eliminates hallucinated citations
- Cross-model adversarial verification (optional)
- Style Calibration — provide 3+ of your past papers and the system learns your writing voice
- Writing Quality Check — warnings for 25 high-frequency AI words, dash control, throat-clearing openings, structural patterns, and burstiness checks
- LaTeX Hardening — APA 7.0
apa7class / IEEE / Chicago - VLM Figure Verification — verifies figures and charts
- Anti-Leakage Protocol — prevents information leakage
- Read-Only Constraint — review agents cannot modify the manuscript, only suggest (mirroring real peer-review boundaries)
- R&R Traceability Matrix — tracks whether each reviewer comment was addressed by the author
- 3 cognitive framework files:
- Toulmin argumentation model + Bradford Hill causal reasoning
- Three-lens review (internal validity / external validity / contribution)
- Research gap definition (real gaps vs. rhetorical gaps)
2. Academic Paper (v3.1.2) — 12-Agent Paper Writing
| Mode | Scenario |
|------|----------|
| full | Complete paper |
| plan | Guided writing |
| outline-only | Outline only |
| revision | Revise per reviewer comments |
| revision-coach | Review-comment analysis |
| abstract-only | Abstract only |
| lit-review | Literature-review paper |
| format-convert | LaTeX / citation format conversion |
| citation-check | Citation checking |
| disclosure | AI disclosure statements (NeurIPS, etc.) |
Core capabilities:
3. Academic Paper Reviewer (v1.9.1) — 7-Agent Multi-Perspective Review
| Role | Responsibility | |------|----------------| | EIC (Editor-in-Chief) | Overall quality gate | | R1 / R2 / R3 | Three dynamic reviewers, each focused on different dimensions | | Devil's Advocate | Challenges the paper across 8 dimensions | | Quality Rubric | 0-100 score: ≥80 Accept, 65-79 Minor, 50-64 Major, <50 Reject |
Core design: