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Conduct a rigorous scientific literature review using arXiv and web search. Use when surveying prior work, finding papers, identifying gaps, or summarizing the state of a research area.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/Bin-Cao/BaiZe --skill literature-reviewコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Use when a user asks to simulate powder diffraction patterns, run GSAS-II Rietveld/Pawley/Le Bail refinement, fit powder diffraction data, inspect GSAS-II service health, or build workflows combining CIF structures with XRD/neutron powder data through the deployed chemistry gateway.
Use when a user asks to parse material formulas, inspect compositions, parse or summarize crystal structures, convert CIF/POSCAR/JSON/CSSR/XSF structures, or analyze symmetry through the deployed chemistry pymatgen gateway service. Triggers on pymatgen, materials, composition, formula parsing, CIF, POSCAR, crystal structure, lattice, space group, symmetry, primitive cell, or structure conversion.
Design and prioritize candidate materials from tabular experimental or computational data. Use when identifying controllable material descriptors and one or more target properties, fitting and validating surrogate models, defining a feasible search space, optimizing single- or multi-objective performance, quantifying uncertainty, or preparing a reproducible materials-discovery recommendation report.
SOC 職業分類に基づく
SKILL.md を表示中
| name | literature-review |
| description | Conduct a rigorous scientific literature review using arXiv and web search. Use when surveying prior work, finding papers, identifying gaps, or summarizing the state of a research area. |
A literature review establishes what is known, how well it is known, and what is not known. Follow this workflow when researching a scientific question.
Scope the question. Write down the research question, the target domain, and inclusion criteria (time range, venue types, key terms). State what kind of evidence would count as an answer.
Search systematically. Use the arxiv tool with targeted queries (ti:, abs:, au:, cat:), the websearch tool for broader discovery, and webfetch for specific papers or venues. Try multiple search phrasings. Record each query and its results in research/review/ so the search is reproducible.
Collect primary sources. Fetch full abstracts (and full text when available) for the most relevant papers. Save structured notes per paper: citation, claims, methods, evidence strength, limitations, open questions.
Synthesize, don't stack. Organize findings by theme, approach, or debate — not by author. Compare competing claims explicitly: what evidence supports each side, and where do they disagree?
Identify gaps. End with concrete open questions: what has no direct evidence, what is contested, and what claims would settle the question?
research/review/ directory with: queries.md (search log), notes/*.md (per-paper notes), and synthesis.md (the final review).