com um clique
paper-scout
// Discover and recommend latest arXiv papers matching user research interests. Use when user says: 推荐今日论文, paper scout, 每日论文, daily papers, paper recommendation.
// Discover and recommend latest arXiv papers matching user research interests. Use when user says: 推荐今日论文, paper scout, 每日论文, daily papers, paper recommendation.
Complete AI research assistant with 6 core capabilities: paper discovery, deep reading notes, reading list management, research taste learning, idea generation, and paper writing. Trigger words: 论文推荐, paper recommendation, arXiv, 读论文, paper notes, DNL, 推荐今日论文, 每日论文, 帮我读一下, paper scout, 论文速读, 帮我安装 ResearchClaw, research claws, researchclaw, 加入待读, 我的论文列表, reading list, 标记已读, 更新我的研究画像, 我的研究画像, research profile, 给我一些研究灵感, idea generator, 跨论文分析, 帮我写论文, paper writing, 论文大纲, 写引言, rebuttal.
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.
Analyze connections across read papers and generate actionable research ideas. Use when user says: 给我一些研究灵感, idea generator, 跨论文分析, research ideas.
Help write research papers: outline, draft sections, auto-review, and rebuttal. Use when user says: 帮我写论文, paper writing, 论文大纲, 写引言, 写方法, 审稿, rebuttal.
Manage a personal reading list with kanban-style statuses and HTML dashboard. Use when user says: 我的论文列表, reading list, 加入待读, 标记已读, 移除.
Maintain and visualize the user research preference profile. Use when user says: 更新我的研究画像, 我的研究画像, research profile.
| name | paper-scout |
| description | Discover and recommend latest arXiv papers matching user research interests. Use when user says: 推荐今日论文, paper scout, 每日论文, daily papers, paper recommendation. |
Before running any capability, load the user's research profile.
Location: ~/.openclaw/workspace/research-claw-config.md
If this file does not exist, use these defaults silently and mention at the end:
💡 想定制推荐兴趣?试试说「更新我的研究画像」
# Default profile (used when no config found)
research_direction: "Large language models, reinforcement learning, agentic AI"
seed_papers: []
keywords:
- large language models
- reinforcement learning
- agentic AI / AI agents
- retrieval-augmented generation
- multimodal models
whitelist_authors: []
learned_preferences:
accept: []
reject: []
Config fields reference:
research_direction — free-text description of the user's research focusseed_papers — list of arXiv IDs the user considers gold-standard referenceskeywords — interest topics used for Paper Scout search querieswhitelist_authors — researcher names to prioritize in recommendationslearned_preferences.accept — keywords/topics user has explicitly likedlearned_preferences.reject — keywords/topics user has skipped or dislikedGoal: Find today's top arXiv papers matching user interests. Output Top 5–10 with relevance scoring.
Triggers: 推荐今日论文 · 每日论文 · paper scout · daily cron job
From the loaded profile, extract keywords and construct arXiv query URLs:
http://export.arxiv.org/api/query?search_query=all:{KEYWORD}&sortBy=submittedDate&sortOrder=descending&max_results=25&start=0
+ (e.g., large+language+models)seed_papers, also fetch their metadata via:
https://export.arxiv.org/abs/{ARXIV_ID}
Use these to calibrate what "relevant" means (topics, methods, problem framing).Use web_fetch for each query URL. Parse the XML Atom response:
<entry>
<title>...</title> <!-- paper title -->
<author><name>...</name></author> <!-- first/all authors -->
<summary>...</summary> <!-- abstract -->
<id>http://arxiv.org/abs/XXXX.XXXXX</id> <!-- canonical URL -->
<published>2026-03-26T...</published> <!-- submission date -->
<arxiv:primary_category term="cs.LG"/> <!-- category -->
</entry>
Filter: Only keep papers published within the last 3 days (compare <published> to today's date in Asia/Shanghai timezone). If fewer than 5 papers remain, extend to 7 days and note it.
Score each paper 1–5 on relevance:
| Signal | Score Boost |
|---|---|
| Title contains exact keyword from user profile | +2 |
| Abstract contains ≥3 keyword matches | +1.5 |
Author in whitelist_authors | +2 |
| Paper cites or builds on seed paper | +1.5 |
| Novel contribution words: "propose", "novel", "outperform", "state-of-the-art", "benchmark" | +0.5 |
| Survey/review signal: "survey", "overview", "analysis of existing" | −1 |
Topic in learned_preferences.accept | +1 |
Topic in learned_preferences.reject | −2 |
Sort descending by score. Keep Top 5 (or Top 10 if user asks for more).
📡 今日论文推荐 | Daily Paper Scout
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🗓️ {DATE} | 匹配兴趣: {COMMA_SEPARATED_KEYWORDS}
1️⃣ **{Title}**
👤 {First Author} et al. ({Year})
🏷️ {category, e.g. cs.LG · cs.AI}
💡 {One-sentence summary — Chinese or English, whichever matches user preference}
🎯 相关原因: {1 sentence — why this matches user's profile}
🔗 {arXiv URL}
2️⃣ **{Title}**
... (repeat)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📝 想深读某篇?发链接说 "帮我读一下" | 加入待读说 "加入待读 [链接]"
If the user reacts to a recommended paper with:
"不错" / "这个好" / "有意思" / "精读" → extract keywords from that paper's title/abstract, add to learned_preferences.accept in config"skip" / "没意思" / "不相关" → extract keywords, add to learned_preferences.rejectUpdate ~/.openclaw/workspace/research-claw-config.md immediately.
If user wants daily delivery:
推荐今日论文| Error | Handling |
|---|---|
| arXiv API returns empty results | Retry once with broader query; if still empty, note "arXiv API temporarily unavailable" |
| PDF tool times out | Fall back to abstract-only mode; note [Abstract only — PDF timeout] in the note |
| PDF tool returns error for a paper | Try fetching https://ar5iv.labs.arxiv.org/html/{ARXIV_ID} as HTML fallback |
| Config file missing | Use defaults silently; add a note at end: "💡 想定制?说「更新我的研究画像」" |
| Reading list JSON missing or malformed | Start fresh with an empty list; inform user: "未找到现有列表,已新建空列表" |
| Template file not found | Report the expected path and ask user to check installation |
| No papers in last 3 days | Extend to 7 days, note it: "(近3天论文较少,已扩展至7天)" |
| Fewer than 3 read papers for Idea Generator | Proceed anyway, but note the limitation |
| User provides PDF/DOI instead of arXiv | Try to extract arXiv ID from DOI or search arXiv by title |