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Computer science bibliography via DBLP API. Use when: user asks about CS publications, author publication lists, or venue (conference/journal) metadata. NOT for: non-CS publications or citation counts.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.
# Academic Literature Search — 学术文献检索与引用管理
Search and retrieve preprints from arXiv via the Atom API. Use this skill when searching for papers in physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering, or economics by keywords, authors, arXiv IDs, date ranges, or categories.
Search arXiv for preprints in physics, math, CS, quantitative biology, quantitative finance, statistics, electrical engineering, economics. Use when: (1) finding preprints by topic, (2) searching by author, (3) browsing arXiv categories, (4) getting paper metadata/abstracts. NOT for: published journal articles (use crossref-search), biomedical (use pubmed-search).
Screen papers for systematic reviews using ASReview active learning. Use when: user has a large set of papers to screen for inclusion/exclusion, wants to prioritize relevant papers, or needs to reduce manual screening workload. NOT for: searching papers (use literature-search) or meta-analysis (use meta-analysis).
Analyzes astronomical observations and cosmological models including telescope data processing, celestial mechanics calculations, stellar evolution, galaxy classification, and cosmological parameter estimation; trigger when users discuss stars, galaxies, exoplanets, dark matter, or the universe's large-scale structure.
| name | dblp-search |
| description | Computer science bibliography via DBLP API. Use when: user asks about CS publications, author publication lists, or venue (conference/journal) metadata. NOT for: non-CS publications or citation counts. |
| metadata | {"openclaw":{"emoji":"💻","requires":{"bins":["curl"]}}} |
Query the DBLP computer science bibliography for publications, authors, and venues.
No API key required. Public REST API.
https://dblp.org/search/
# Search by keyword
curl -s "https://dblp.org/search/publ/api?q=attention+is+all+you+need&format=json&h=5" | python3 -c "
import json,sys
data=json.load(sys.stdin)
for hit in data['result']['hits'].get('hit',[]):
info=hit['info']
print(f\"Title: {info.get('title','')}\")
print(f\"Authors: {', '.join(a.get('text','') for a in info.get('authors',{}).get('author',[]))}\")
print(f\"Venue: {info.get('venue','')}, Year: {info.get('year','')}\")
print()
"
# Filter by year
curl -s "https://dblp.org/search/publ/api?q=large+language+model+year%3A2024&format=json&h=10"
# Find author
curl -s "https://dblp.org/search/author/api?q=Yoshua+Bengio&format=json&h=5"
# Get author's publication list
curl -s "https://dblp.org/pid/b/YoshuaBengio.xml?format=json" | python3 -c "
import json,sys
data=json.load(sys.stdin)
pubs=data.get('dblpperson',{}).get('r',[])[:10]
for p in pubs:
entry=list(p.values())[0] if isinstance(p,dict) else {}
print(f\"{entry.get('year','')} - {entry.get('title','')}\")
"
# Find conference/journal
curl -s "https://dblp.org/search/venue/api?q=NeurIPS&format=json&h=5"
# h = results per page, f = first result index
curl -s "https://dblp.org/search/publ/api?q=graph+neural+network&format=json&h=20&f=0"
curl -s "https://dblp.org/search/publ/api?q=graph+neural+network&format=json&h=20&f=20"