Paper Reading

Paper Reading

Structured workflow for reading academic papers efficiently.

When to Use

• User shares an arXiv link or PDF and asks to read/summarize it
• User asks about a specific paper's contributions, methods, or results
• User wants a reading digest for their records
• User asks to compare a paper against related work

Reading Levels

Level 1: Quick Skim (2 min)

When: User just wants to know if a paper is worth reading

Output:

• Paper title, authors, venue, year
• One-paragraph summary (what problem, what method, what result)
• Key contribution in one sentence
• Relevance assessment to user's work
• Recommendation: Read / Skip / Skim only

Level 2: Standard Read (10 min)

When: User wants to understand the paper's approach

Output:

• Problem: What gap does this address?
• Method: How do they solve it? (with key technical details)
• Key innovation: What's genuinely new vs. incremental?
• Results: Main numbers + comparison to baselines
• Limitations: What they don't do, acknowledged or not
• Connections: How does this relate to user's active projects?

Level 3: Deep Analysis (30 min)

When: User is seriously considering building on this paper

Output:

• Everything from Level 2, plus:
• Detailed methodology: Step-by-step technical walkthrough
• Reproducibility assessment: Can you implement this from the paper alone?
• Experimental design critique: Are the baselines fair? Metrics appropriate?
• Hidden assumptions: What are they not saying?
• Extension opportunities: How could this be improved or adapted?
• Key equations/algorithms: Extracted and explained
• Figure analysis: What do the key figures actually show?

Workflow

Step 1: Obtain Paper

arXiv link → Download PDF, extract text
PDF file → Extract text directly
Paper title → Search Semantic Scholar → get arXiv link → download
Zotero item → Get from local library

Step 2: Read at Requested Level

Follow the appropriate level template above. When in doubt, start with Level 2.

Step 3: Store Digest

After reading, save the digest:

1. Store structured summary to local dashboard
2. If user confirms, add/update Zotero entry with notes

Step 4: Connect to Context

• Link to user's active projects if relevant
• Suggest follow-up papers (from references or "cited by")
• Note if this paper supports or contradicts prior reads

Reading Heuristics

For ML/AI papers:

• Jump to Table 1 (main results) first — if the numbers aren't impressive, calibrate expectations
• Check the ablation study — it reveals what actually matters in their method
• Read the limitations/future work section — often more honest than the intro
• Look at Appendix — important details are often buried there

For methods papers:

• Focus on Figure 1 (method overview) + Section 3 (method) + Table 1 (results)
• Skip related work on first pass — come back only if you need positioning context

For empirical papers:

• Focus on experimental setup, metrics, and statistical significance
• Check if baselines are fairly implemented (same hyperparameter search budget?)
• Look for cherry-picked examples in qualitative analysis

Paper Comparison Mode

When user asks to compare two papers:

| Aspect       | Paper A          | Paper B          |
|--------------|------------------|------------------|
| Problem      |                  |                  |
| Method       |                  |                  |
| Data         |                  |                  |
| Key metric   |                  |                  |
| Advantage    |                  |                  |
| Limitation   |                  |                  |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: jxtse
• Source: jxtse/scientific-research-skills
• License: MIT

Install and usage instructions live in the source repository linked above.