# Paper RAG

> RAG-powered multi-paper knowledge base for academic literature: cross-paper QA, literature corpus management, topic accumulation, and evidence retrieval.

- Skill: `marvin-lijunzan/paper-rag` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add marvin-lijunzan/paper-rag`
- Raw SKILL.md: https://api.skillmd.com/api/skills/marvin-lijunzan/paper-rag/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: Marvin-LiJunZan (https://skillmd.com/u/marvin-lijunzan)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/marvin-lijunzan/paper-rag

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# Paper RAG — Literature Knowledge Base & Multi-Paper QA

Paper RAG transforms your collection of research papers (PDFs, Markdown notes, BibTeX libraries) into a queryable, evidence-grounded research knowledge base.

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## Capabilities

1. **Cross-Paper Synthesized QA**:
   - Ask questions across dozens of papers simultaneously (e.g., *"How do different studies handle the water-to-binder ratio in alkali-activated slag?"*).
   - Returns responses strictly grounded in retrieved chunks with exact paper citation keys and section references.

2. **Long-Term Topic Knowledge Accumulation**:
   - Maintains an incremental index of papers in `corpus/`.
   - Supports adding new papers, tagging by sub-topics, and tracking conflicting findings across publications.

3. **Evidence Matrix Aggregation**:
   - Automatically gathers comparative data (metrics, datasets, parameter ranges) across papers into structured markdown tables.

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## Quick Usage

Run the bundled lightweight Python RAG engine:

```powershell
# Index a directory of papers or notes
python scripts/paper_rag.py index --dir "path/to/papers" --db "paper_index.json"

# Query the literature base
python scripts/paper_rag.py query --db "paper_index.json" --query "How is compressive strength affected by curing temperature?"
```

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## Query Modes

- **Synthesize Mode**: Merges viewpoints from multiple authors, highlighting agreements and controversies.
- **Compare Mode**: Constructs a head-to-head table of methodologies, assumptions, and outcomes.
- **Fact-Check Mode**: Locates whether any paper in your corpus supports or contradicts a specific claim.