Compare academic research papers side-by-side to identify similarities, differences, and research gaps. Use when user wants to compare 1-5 papers via DOIs, URLs, search queries, or PDF files. Supports mixed input types. Outputs both comparison table and detailed narrative summary.
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Compare academic research papers side-by-side to identify similarities, differences, and research gaps. Use when user wants to compare 1-5 papers via DOIs, URLs, search queries, or PDF files. Supports mixed input types. Outputs both comparison table and detailed narrative summary.
version
1.2.1
changelog
Added user_goal to history, clarified step structure
metadata
{"clawdbot":{"emoji":"📄","category":"research"}}
Paper Compare
Compare academic papers side-by-side with structured tables and detailed narrative analysis.
The Paper Comparison Reasoning Framework
┌─────────────────────────────────────────────────────────────┐
│ PAPER COMPARISON THINKING │
├─────────────────────────────────────────────────────────────┤
│ 1. INTERPRET → What papers? What comparison goal? │
│ 2. RETRIEVE → Fetch metadata, abstracts, full text │
│ 3. ANALYZE → Extract across 10 dimensions │
│ 4. SYNTHESIZE → Build narrative, find gaps, score quality │
│ 5. VALIDATE → Check completeness, deliver │
└─────────────────────────────────────────────────────────────┘
Decision Tree: Input Processing
USER INPUT
│
├── 1 paper ──→ Single Paper Summary
│ └── Skip comparison, show full summary
│
├── 2-5 papers ──→ Full Comparison
│ └── Proceed with 10 dimensions
│
├── >5 papers ──→ Ask to Narrow
│ └── "Please narrow to 2-5 for meaningful comparison"
│
├── DOI ──→ Fetch via crossref/semantic scholar
│ └── https://api.crossref.org/works/{doi}
│
├── URL ──→ Fetch via web_fetch
│ └── Extract title, authors, abstract
│
├── Search query ──→ Search first
│ └── Use web_search, present top 3, CONFIRM before proceeding
│
└── PDF file ──→ Extract text first
└── Use pdf skill, then extract metadata
Decision Tree: Comparison Angle
WHAT IS THE COMPARISON ABOUT?
│
├── Same topic, different methods ──→
│ └── Focus: methodology differences, results comparison
│
├── Same method, different domains ──→
│ └── Focus: adaptation, performance across domains
│
├── Evolution over time ──→
│ └── Focus: improvements, what changed, SOTA progression
│
├── Competing approaches ──→
│ └── Focus: trade-offs, when to choose which
│
└── Complementary papers ──→
└── Focus: how they combine, gaps each fills
Must have:
├── Title
├── Authors
├── Year
├── Venue
├── Abstract (for methodology + results)
Nice to have:
├── Full text (for limitations)
├── Code/data links
├── Citation count (see below)
## Overview
[What problem each paper addresses - high-level]
[Comparison angle: what are we comparing?]
## Methodology Comparison
[Compare techniques - are they compression-based? architecture-based?
What's the key algorithmic difference?
How does the comparison angle affect this?]
## Results Analysis
[Quantitative results - specific numbers, metrics
Performance comparison - trade-offs mentioned
Which paper wins on what?]
## Limitations
[What each paper acknowledges - be honest about gaps]
[What's NOT covered that might matter]
## Research Gaps
[What's MISSING across ALL papers]
[What's not yet explored]
[Potential future directions]
## Quality Assessment
[Paper A: ⭐⭐⭐ - Why]
[Paper B: ⭐⭐ - Why]
[Note any concerns]
Step 5: Structured Verdict
Decision Matrix
Decision Matrix
| If You Need... | Choose | Why |
|----------------|--------|-----|
| [Best performance] | Paper [X] | [Reason] |
| [Easiest to implement] | Paper [X] | [Reason] |
| [Latest method] | Paper [X] | [Reason] |
| [Most cited/reliable] | Paper [X] | [Reason] |
| [Code available] | Paper [X] | [Reason] |
Final Recommendation
## Verdict**For [user's goal]:**-**Best overall:** [Paper X] — [key reason]
-**Best for implementation:** [Paper Y] — [key reason]
-**Best for research depth:** [Paper Z] — [key reason]
**My recommendation:** [Paper X] because [specific reason matching user's goal]
**If you're unsure:** Start with [Paper X] for [reason], then explore [Paper Y] if you need [different aspect].
Self-Check: Before Delivering
Did I answer the user's original question?
Did I identify the comparison angle?
Are all 10 dimensions covered?
Is quality scored?
Is verdict actionable?
Step 6: Validate & Deliver
For Single Paper (1 only)
Output:
## Paper Summary
**Title:** [title]
**Authors:** [authors]
**Year:** [year]
**Venue:** [venue]
### Research Question
[What problem they address]
### Methodology
[Brief description]
### Key Results
[With numbers]
### Limitations
[What they acknowledge]
### Code & Data
[Links or "Not specified"]
### Citation Count
[If available]
### Quality Score
[⭐⭐⭐]
FETCH FAILS
│
├── DOI not found ──→ Check DOI format, try search
│ └── "DOI not found. Did you mean...?"
│
├── URL inaccessible ──→ Try alternative source
│ └── e.g., arXiv → semantic scholar
│
├── Search returns nothing ──→ Try different keywords
│ └── "No papers found for [query]. Try...?"
│
└── PDF extraction fails ──→ Note "Unable to extract"
└── Can still use metadata if available
History (Persistence)
Save After Comparison
{"last_comparison":{"date":"2026-03-04","user_goal":"[what user wanted to achieve - learning/research/writing/decision]","papers":[{"title":"...","doi":"10.xxxx/xxx"},{"title":"...","url":"..."}],"topic":"[what was compared]","comparison_angle":"[same topic different methods / etc]","verdict":"[which paper recommended]","dimensions":{"methodology":"...","key_difference":"..."}}}
Load History
Read memory/paper-compare-history.json if exists
Use memory_search to find prior comparisons
Dependencies
Skill
Use For
pdf
Extract text from uploaded PDFs
web_search
Find papers by query
web_fetch
Get paper content from URLs
Quick Reference
Input
Action
1 DOI
Single summary
2 DOIs
Full comparison
arXiv URL
Fetch abstract
"search for X"
Search → confirm → proceed
Upload PDF
Extract → analyze
Summary Checklist
Identify comparison angle
Retrieve all papers (metadata + abstract)
Extract 10 dimensions
Score quality (venue, citations, code, data)
Build comparison table
Write narrative summary
Create structured verdict
Save to history
Notes
Always confirm before proceeding with search results
Keep comparisons focused: 2-5 papers max
Don't infer missing information — state "Not specified"
Save to history for future reference
Quality scoring helps users make informed decisions