| name | paper-compare |
| slug | paper-compare |
| triggers | /paper-compare |
| author | ClawHub community |
| license | Community-vendored |
| hub_pack | clawhub-research |
| trust_level | community |
| upstream_url | https://clawhub.ai/skills/paper-compare |
| audit_status | reviewed |
| description | 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
Self-Check: After Identifying Angle
Step 1: Interpret the Request
What to Clarify
| Question | Why It Matters |
|---|
| Which papers? | Need exact references |
| What goal? | Learning? Research? Writing? |
| What comparison angle? | Focus analysis appropriately |
Self-Check: Before Starting
Step 2: Retrieve Papers
Retrieval Strategy
| Input Type | Method | Source |
|---|
| DOI | API | crossref, semantic scholar |
| URL | web_fetch | arXiv, IEEE, PubMed |
| Search | web_search → web_fetch | Find, then confirm |
| PDF | pdf skill | Extract text |
| History | memory_search | Prior comparisons |
Quality Priority
Must have:
├── Title
├── Authors
├── Year
├── Venue
├── Abstract (for methodology + results)
Nice to have:
├── Full text (for limitations)
├── Code/data links
├── Citation count (see below)
Citation Count
Use Semantic Scholar API:
https://api.semanticscholar.org/graph/v1/paper/{doi}?fields=citationCount
Self-Check: After Retrieval
Step 3: Analyze (10 Dimensions)
Core Dimensions (Always Include)
| # | Dimension | What to Extract |
|---|
| 1 | Title | Full title |
| 2 | Authors | All authors, first author highlighted |
| 3 | Year | Publication year |
| 4 | Venue | Journal/Conference |
| 5 | Research Question | What problem do they solve? |
| 6 | Methodology | Approach, techniques used |
| 7 | Dataset | What data did they use? |
| 8 | Results | Key findings with numbers |
| 9 | Limitations | What do they acknowledge? |
| 10 | Code & Data | Links to artifacts? |
Decision: What If Missing?
Missing dimension:
│
├── Abstract missing ──→ Note "Unable to analyze methodology"
│
├── Results missing ──→ Note "Results not available in metadata"
│
├── Limitations missing ──→ Note "Not specified" (don't infer)
│
└── Dataset unclear ──→ Note "Not clearly specified"
Step 4: Synthesize
Quality Scoring
Evaluate each paper:
| Factor | Score | Notes |
|---|
| Venue Quality | | |
| - Top-tier (NeurIPS, ICML, ICLR, Nature, Science) | ⭐⭐⭐ | |
| - Good (AAAI, IJCAI, CVPR, EMNLP, IEEE) | ⭐⭐ | |
| - Other | ⭐ | |
| Citations | | |
| - 100+ | ⭐⭐⭐ | Highly cited |
| - 10-100 | ⭐⭐ | Well-known |
| - <10 | ⭐ | Recent or niche |
| Code Available | | |
| - Yes, official | ⭐⭐⭐ | |
| - Yes, community | ⭐⭐ | |
| - No | ⭐ | |
| Data Available | | |
| - Yes | ⭐⭐⭐ | |
| - No | ⭐ | |
Overall Quality: Sum stars (higher = more established)
Comparison Table Structure
| Dimension | Paper A | Paper B | ... |
|-----------|---------|---------|-----|
| Title | ... | ... | ... |
| Authors | ... | ... | ... |
| Year | ... | ... | ... |
| Venue | ... | ... | ... |
| Research Question | ... | ... | ... |
| Methodology | ... | ... | ... |
| Dataset | ... | ... | ... |
| Results | ... | ... | ... |
| Limitations | ... | ... | ... |
| Code & Data | ... | ... | ... |
| Quality Score | [⭐⭐⭐] | [⭐⭐] | ... |
Narrative Synthesis Template
Structure:
## 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
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
[⭐⭐⭐]
For Comparison (2-5 papers)
Deliver:
- Comparison Angle — What we're comparing and why
- Comparison Table — All 10 dimensions + quality
- Narrative Summary — 6-section synthesis
- Quality Assessment — Scored factors
- Structured Verdict — Decision matrix + recommendation
Edge Cases to Note
| Situation | How to Handle |
|---|
| Different fields | Warn: "Comparing CS vs Biology papers" |
| Very different years | Note: "2010 vs 2024 — comparison may be unfair" |
| Preprint | Note: "Preprint — not peer-reviewed" |
| Conflicting results | Note: "Paper A claims X, Paper B claims Y" |
Error Handling
If Retrieval Fails
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
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
