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COPYRIGHT NOTICE
Basé sur la classification professionnelle SOC
# Academic Literature Search — 学术文献检索与引用管理
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.
"Astronomical computations via Astropy. Use when: user asks about celestial coordinates, FITS files, or cosmological calculations. NOT for: telescope control or real-time observation planning."
Performs bioinformatics analyses including pathway enrichment, gene ontology analysis, protein-protein interaction networks, multi-omics integration, and biological sequence database querying; trigger when users discuss gene sets, biological pathways, functional annotation, or omics data integration.
| name | deep-research-swarm |
| description | COPYRIGHT NOTICE |
name: deep-research-swarm description: Multi-agent research literature analysis keywords:
A coordinated swarm of agents designed to perform deep, parallelized research into biomedical literature, aggregating findings into comprehensive reports.
User: "Research the latest advancements in mRNA cancer vaccines."
Agent Action:
python3 src/research/agents/agent_coordinator.py --topic "mRNA cancer vaccines" --depth "deep"