jxtse/scientific-research-skills/paper-reading

Claude Code and agent skill by jxtse/scientific-research-skills

Trust tier 2
  • community
LLM review pending
Source check pending

Checking that the SKILL.md file is still in the repository.

Reads and analyzes academic papers (arXiv preprints, conference / journal PDFs, Zotero items) at three configurable depths: quick skim (2 min), standard read (10 min), or deep analysis (30 min). Produces structured digests covering problem, method, key innovation, results, limitations, reproducibility, hidden assumptions, and connections to the user's other work. Use when the user shares an arXiv link, PDF, or paper title and asks to read / summarize / digest / TL;DR / analyze / review / critique / explain / break down a paper, asks about a paper's contributions / methods / results / equations / figures, wants to compare two papers side by side, or needs a reading note for their records.

Install

npx vskill@latest install jxtse/scientific-research-skills/paper-reading

SKILL.md

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 | | |

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

7-day trend score
0

Not refreshed yet.

Works with

Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.

  • Claude Code
  • Cursor
  • GitHub Copilot
  • Windsurf
  • Codex
  • Gemini CLI
  • Cline
  • Amp
  • Roo Code
  • Goose
  • Continue
  • Kilo Code
  • Junie
  • Trae
  • OpenHands
  • Qwen Code
  • AI Agent
  • Tabnine Chat
  • Sourcegraph Cody
  • Amazon Q
  • Firebase Genkit
  • Sweep
  • Devin
  • Phind
  • Mentat
  • Claude Desktop
  • Aider
  • GPT Pilot
  • Plandex
  • bolt.new
  • v0
  • Replit Agent
  • Anse
  • TypingMind
  • BetterChatGPT
  • LibreChat
  • Warp AI
  • Pieces
  • Fig AI
Embed badge
vskill VERIFIED badge
[![vskill VERIFIED](https://verified-skill.com/api/v1/skills/jxtse/scientific-research-skills/paper-reading/badge)](https://verified-skill.com/skills/jxtse/scientific-research-skills/paper-reading)

Something wrong with this skill or its page? Tell us.