--- name: paper-reader description: > 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. --- # 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.XXXXX` - `https://arxiv.org/pdf/2503.XXXXX` → `2503.XXXXX` - `https://arxiv.org/pdf/2503.XXXXX.pdf` → `2503.XXXXX` - Bare ID: `2503.XXXXX` --- ## Step 2 — Fetch Metadata ``` web_fetch: https://arxiv.org/abs/{ARXIV_ID} ``` 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 ```markdown # Deep Note — {ALIAS} ## 0) Metadata - **Title:** {FULL_TITLE} - **Alias:** {ALIAS} - **Authors / Org:** {AUTHORS} ({INSTITUTIONS}) - **Venue / Status:** {VENUE_OR_ARXIV_ID} ({STATUS}) - **Date:** {PAPER_DATE} - **Links:** - Abs: https://arxiv.org/abs/{ARXIV_ID} - HTML: https://arxiv.org/html/{ARXIV_ID}v1 - PDF: https://arxiv.org/pdf/{ARXIV_ID} - Code: {CODE_URL_OR_PROJECT_PAGE} - **Tags:** {comma-separated tags} - **My rating:** {STARS} ({N}/5) - **Read depth:** deep - **Scoring ({BREAKDOWN}):** {EXPLANATION} = **{N}/5** --- ## 1) 一句话 Why-read - **Key claim/contribution + key observation:** {ONE_PARAGRAPH} --- ## 2) CRGP 拆解 Introduction ### C — Context {2-3 sentences on research background} ### R — Related work {Bullet list grouped by methodology line} ### G — Gap {2-3 sentences on specific limitations} ### P — Proposal {2-3 sentences on proposed solution + key insight} --- ## 3) Figure 区 {For each key figure:} - 图N({description}): ![figN]({arxiv_html_figure_url}) {One-line interpretation} --- ## 4) Experiments — Key Numbers ### Main Results | Benchmark | Metric | This Work | Best Baseline | Delta | |-----------|--------|-----------|---------------|-------| | ... | ... | ... | ... | ... | ### Ablation {Key ablation findings with numbers} ### Limitations {2-3 honest limitations} --- ## 5) Why it matters — 对我研究的启发 {2-4 numbered insights connecting to reader's research} ## 6) Actionable next step - [ ] {Follow-up item 1} - [ ] {Follow-up item 2} - [ ] {Follow-up item 3} ## 7) 评分解释 **{N}/5({BREAKDOWN})** {Bullet explanation for each component} ``` ### Key rules for markdown deep note: 1. **Use real numbers** — never write "XX" or placeholders 2. **Figures must have URLs** from arxiv HTML version when available 3. **Tables use pipe format** — compatible with GitHub/Obsidian 4. **Chinese + English mixed** — technical terms in English, analysis in Chinese 5. **Scoring breakdown must be explicit** — show the math ---## Step 5 — Output Chat Summary After writing the markdown file, output a brief summary in chat: ``` 📝 Deep Note 完成 | {ALIAS} ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📌 **{TITLE}** 👤 {AUTHORS} | 📅 {YEAR} | ⭐ {RATING} 🔗 https://arxiv.org/abs/{ARXIV_ID} 💡 **核心发现:** {WHY_READ one sentence} 📊 **关键数据:** {BEST_RESULT metric + number} ✨ **启发:** {TOP_INSIGHT one sentence} 💾 笔记 → {OUTPUT_PATH} ``` --- ## Step 6 — (Optional) Generate HTML Only if user requests HTML (`--html` / `生成 HTML` / `生成网页`): 1. Load template from `{SKILL_DIR}/../../templates/paper-note.html` 2. Fill all `{{PLACEHOLDER}}` tags using extracted content 3. Save to output directory as `{ARXIV_ID}.html` 4. 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