alphalab-ustc/researchclaw/paper-reader
Claude Code and agent skill by alphalab-ustc/researchclaw
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Checking that the SKILL.md file is still in the repository.
Deep-read an arXiv paper and generate structured Deep Note reading notes. Default output: markdown deep note file (low token cost, git-friendly). Optional: HTML page from template. Trigger: 帮我读一下, DNL, 论文速读, paper notes, or an arXiv link.
Install
npx vskill@latest install alphalab-ustc/researchclaw/paper-readerSKILL.md
Paper Reader — Deep Reading Notes (v3.1)
Overview
Given an arXiv paper, produce a structured deep reading note as a markdown file. Optionally generate an HTML page from the paper-note template.
Default output format: Markdown Deep Note (saves tokens, git-friendly, composable). HTML output: Add --html or say 生成 HTML to also produce an HTML page.
Triggers: arXiv link · 帮我读一下 · DNL · 论文速读 · paper notes
Step 0 — Load Research Profile (Always First)
Before running, load: ~/.openclaw/workspace/research-claw-config.md
If missing, use defaults silently and mention at the end:
Want to customize? Say "更新我的研究画像"
Step 1 — Extract arXiv ID
Recognize patterns:
https://arxiv.org/abs/2503.XXXXX→2503.XXXXXhttps://arxiv.org/pdf/2503.XXXXX→2503.XXXXXhttps://arxiv.org/pdf/2503.XXXXX.pdf→2503.XXXXX- Bare ID:
2503.XXXXX
Step 2 — Fetch Metadata
Extract: title, authors, year, abstract, subject categories, venue if mentioned. Also fetch HTML version for figures: https://arxiv.org/html/{ARXIV_ID}v1
---## Step 3 — Analyze Paper Content
Use web_fetch on the HTML version for structured content extraction. Focus on: Abstract, Introduction, Method, Experiments (tables/numbers), Conclusion.
Extract using the Deep Note 7-section framework:
| Section | What to extract | |
|---|---|---|
| 0) Metadata | Title, alias, authors, venue, date, links, tags, rating, scoring breakdown | |
| 1) Why-read | One-sentence: key claim + key observation | |
| 2) CRGP | Context, Related work, Gap, Proposal — from Introduction | |
| 3) Figures | Key figures with URLs from arxiv HTML + one-line descriptions | |
| 4) Experiments | Main results table, ablation highlights, limitations | |
| 5) Why it matters | Research insights for the reader's own work (2-4 bullets) | |
| 6) Next steps | Actionable follow-up items as checkboxes | |
| 7) Scoring | Rating breakdown explanation |
Scoring System
Base score: 1 (any complete paper with benchmarks)
Quality bonus (0-2):
- +1: Solid experiments with proper ablation
- +2: Strong ablation + SOTA results + novel methodology
Observation bonus (0-2):
- +1: Finding directly relevant to reader's research
- +2: Paradigm-shifting insight for the field
Final = Base + Quality + Observation (max 5/5)
---## Step 4 — Write Markdown Deep Note File
Output directory: Same repo as reading notes (e.g., papers/ directory). Filename: YYYY-MM-DD_{alias}.md (e.g., 2026-04-01_gems.md)
Markdown Deep Note Template
Key rules for markdown deep note:
- Use real numbers — never write "XX" or placeholders
- Figures must have URLs from arxiv HTML version when available
- Tables use pipe format — compatible with GitHub/Obsidian
- Chinese + English mixed — technical terms in English, analysis in Chinese
- Scoring breakdown must be explicit — show the math
---## Step 5 — Output Chat Summary
After writing the markdown file, output a brief summary in chat:
Step 6 — (Optional) Generate HTML
Only if user requests HTML (--html / 生成 HTML / 生成网页):
- Load template from
{SKILL_DIR}/../../templates/paper-note.html - Fill all
{{PLACEHOLDER}}tags using extracted content - Save to output directory as
{ARXIV_ID}.html - Report the saved path
See the root SKILL.md for the full placeholder mapping table.
Error Handling
| Error | Action | |
|---|---|---|
| arXiv HTML unavailable | Use abstract page only; note [HTML unavailable] | |
| Very long paper (>50 pages) | Focus on Abstract, Intro, Method, Results tables, Conclusion | |
| No figures found in HTML | Skip Figure section, note [No figures extracted] | |
| Config file missing | Use defaults; suggest "更新我的研究画像" |
Token Efficiency Notes
- Markdown deep note costs ~2-3K output tokens (vs ~8-10K for HTML template filling)
- Markdown files are git-friendly: diff, merge, grep all work naturally
- Reading list tables can directly link to markdown notes via relative paths
- HTML generation is now opt-in, not default — saves tokens on every paper read
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
- SKILL.md in the repositoryCheckingskills/paper-reader/SKILL.md
Popularity
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