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概要と使いどころ
Use when targeting Earth and Planetary Science Letters (EPSL) or deciding whether a quantitative solid-earth or planetary-science manuscript fits this venue. Encodes the journal's broad-interest process-science fit, the quantitative geochemistry/geophysics evidence bar, Elsevier house style, official-submission re-check, and desk-reject heuristics.
日本語の概要は準備中です。原文の説明を表示しています。
Neo4j Graph Data Science (GDS) embedded plugin via Python client or Cypher — covers graphdatascience client 2.x, GraphDataScience, gds.graph.project.native, gds.graph.project.cypher, snake_case endpoints, graph catalog operations, stream/stats/mutate/write modes, memory estimation, PageRank, Louvain, WCC, FastRP, KNN, Node Similarity, ML pipelines, and cleanup. Use for Aura Pro, self-managed, local, or offline Neo4j DBMS with the GDS plugin installed. Does NOT cover Aura Graph Analytics GDS Sessions, AuraGraphDataScience, GdsSessions, gds.graph.project.remote, or AuraDB Cypher API projection/session management — use neo4j-aura-graph-analytics-skill. Does NOT handle Cypher authoring — use neo4j-cypher-skill. Does NOT cover driver setup — use neo4j-driver-python-skill or other driver skill.
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Use when interpreting biological research findings, evaluating life science evidence, analyzing molecular or cellular mechanisms, comparing competing biological hypotheses, designing or critiquing experiments in biology, genetics, genomics, cell biology, immunology, neuroscience, ecology, or any life science domain. Triggers on questions about gene function, pathways, phenotypes, GWAS hits, single-cell data, animal models, clinical translation, evolutionary arguments, or any biology/life science reasoning task.
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Record insect sightings with location, date, habitat, photography, behavior notes, preliminary identification, and citizen science submission. Covers GPS coordinates, weather conditions, microhabitat description, macro photography techniques, behavioral observations, preliminary identification to order using body plan, and submission to citizen science platforms such as iNaturalist. Use when encountering an insect you want to document, contributing to citizen science biodiversity databases, building a personal observation journal, or supporting ecological surveys with georeferenced photographic records.
日本語の概要は準備中です。原文の説明を表示しています。
Use when installing Anthropic's Claude Science on a geo-blocked machine (e.g. China) or running it without a Claude account. Downloads the binary from the unblocked downloads.claude.ai CDN, sets up the claude-science-api-bridge local proxy to route requests to ANY OpenAI- or Anthropic-compatible API (Volcengine, DeepSeek, Kimi, Zhipu, OpenAI, local Ollama/vLLM), and applies a no-login patch so no Claude Pro/Max subscription is required.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level neuroscience covering neuronal physiology, synaptic transmission, brain regions and circuits, neuroplasticity, neurodegenerative diseases, and computational neuroscience.
日本語の概要は準備中です。原文の説明を表示しています。
Gregor Mendel — genetics mentor, patient experimenter, and gardener-monk. Trigger this skill when users ask about genetics, heredity, inheritance patterns, Mendelian laws, dominant/recessive traits, gene segregation, independent assortment, Punnett squares, classical genetics, or evolution-genetics connections. Also trigger when discussing the philosophy of science, how great ideas get ignored, the relationship between faith and science, or the virtue of patient long-term observation. Even if the user doesn't say "Mendel" explicitly, trigger this skill for questions touching genetics, breeding, trait inheritance, or genomics history. Part of the AIPOCH Science Mentor Skill Hub.
日本語の概要は準備中です。原文の説明を表示しています。
Use when targeting Trends in Food Science & Technology or deciding whether a food-science review manuscript fits this venue. Encodes the journal's review-only fit, the critical-synthesis and comprehensiveness bar, structure expectations, official-submission re-check, and desk-reject heuristics.
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Data Science Virtual Machines development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when managing DSVM images/tools, IaC deployment (Bicep/ARM), Key Vault secrets, MLflow, or GPU/Jupyter issues, and other Azure Data Science Virtual Machines related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Machine Learning (use azure-machine-learning), Azure Databricks (use azure-databricks), Azure HDInsight (use azure-hdinsight).
日本語の概要は準備中です。原文の説明を表示しています。
将 Web of Science 数据库导出的纯文本格式（包含 AU, TI, SO 等标签）转换为标准的参考文献引用格式。
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Screens biomedical / life-science papers for signs of data fabrication, image manipulation, and statistical anomalies, using the detection techniques distilled from the field's canonical exposure platforms (PubPeer, Data Colada, Science Integrity Digest, For Better Science) and tools (ImageTwin/Proofig, statcheck, GRIM/GRIMMER, Problematic Paper Screener, Seek & Blastn). Use when asked to check a paper/figure for image duplication, blot splicing, impossible statistics, paper-mill or tortured-phrase signals, research integrity, or "is this data faked"; or when a user shares a figure, Western blot, supplementary dataset, or DOI and asks whether it looks manipulated. Reports observable anomalies as questions for clarification — it never accuses anyone of fraud.
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Use for social science academic paper drafting, outlining, diagnosis, review, and revision. Trigger for topic diagnosis, research question refinement, literature review planning, CNKI/Google Scholar literature search-to-Zotero workflows, structured paper reading notes, theoretical framework design, research design critique, draft review, section or paragraph revision, citation and evidence risk checking, causal-claim checking, and pre-submission review. Do not use for purely creative writing or non-academic editing.
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Use the DataSciencePython tutorial/example collection through modern self-contained helpers for Python data-science resources, statsmodels logistic regression, scikit-learn Kaggle-style tabular classifiers, and Twitter JSONL extraction.
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Use Cookiecutter Data Science to generate, configure, validate, and troubleshoot reproducible data-science project templates and generated project workflows.
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Think and work like an expert Building Science Engineer. Use when a task calls for Building Science Engineer judgment. Reasons from coupled heat-air-moisture transport through ASHRAE 160 moisture-design analysis, WUFI transient simulation, ACH50 leakage mapping, and ISO 10211 psi-values while treating exfiltration condensation, reservoir claddings, and mold-index sensitivity as first-class failure modes.
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中医诊疗 — 中医临床医师的认知操作系统 (经典理论 阴阳五行脏腑气血经络六经卫气营血三焦 + 四诊八纲 + 治法 + 方剂学 经方时方 + 中药学 四气五味归经炮制 + 针灸学 经络穴位手法灸法 + 推拿按摩 + 中医各科 内外妇儿骨伤皮肤眼耳鼻喉肛肠老年急症 + 中西医结合 + 循证中医 + NATCM 监管 + 中医诊所备案 + 国家级名老中医 学术继承人 — 不含 道家修炼 / 风水算命 / 中医养生科普 / 中医美容 / 民族医学藏蒙维傣) (Traditional Chinese Medicine (TCM) clinical practice — the cognitive operating system of practicing TCM physicians covering (a) 经典理论 (阴阳/五行/脏腑/气血津液/经络/六淫/七情/六经/卫气营血/三焦) classical theory, (b) 四诊 (望闻问切) clinical observation/inquiry/pulse + 八纲 (阴阳/表里/寒热/虚实) syndrome differentiation, (c) 治法 (汗吐下和温清消补 + 扶正祛邪) therapeutic principles, (d) 方剂学 (经方 时方 验方) formula science, (e) 中药学 (四气五味/归经/七情/炮制/配伍禁忌) materia medica, (f) 针灸学 (经络穴位/手法/灸法/电针) acupuncture+moxibustion, (g) 推拿按摩 tuina massage, (h) 中医各科 (内/外/妇/儿/骨伤/皮肤/眼/耳鼻喉/肛肠/老年/急症) clinical specialties, (i) 中西医结合 integrative medicine, (j) 循证中医 + 临床流行病学 evidence-based TCM + 现代研究, (k) 中医诊所备案 / 中医师资格 / NATCM 监管 / 药典 / GMP regulatory framework, (l) 国家级名老中医 学术继承人 项目 transmission program; NOT 道家修炼 / 风水 / 算命八字 (那是 玄学不是 中医), NOT 中医养生科普 (是 衍生 不是 临床主体), NOT 中医美容 (是 商业化分支), NOT 民族医学 (藏蒙维傣 是 平行体系 不在本 skill 主线 — 仅作 边界标注).) Master OS — automated mastery of Traditional Chinese Medicine (TCM) clinical practice — the cognitive operating system of practicing TCM physicians covering (a) 经典理论 (阴阳/五行/脏腑/气血津液/经络/六淫/七情/六经/卫气营血/三焦) classical theory, (b) 四诊 (望闻问切) clinical observation/inquiry/pulse + 八纲 (阴阳/表里/寒热/虚实) syndrome differentiation, (c) 治法 (汗吐下和温清消补 + 扶正祛邪) therapeutic principles, (d) 方剂学 (经方 时方 验方) formula science, (e) 中药学 (四气五味/归经/七情/炮制/配伍禁忌) materia medica, (f) 针灸学 (经络穴位/手法/灸法/电针) acupuncture+moxibustion, (g) 推拿按摩 tuina massage, (h) 中医各科 (内/外/妇/儿/骨伤/皮肤/眼/耳鼻喉/肛肠/老年/急症) clinical specialties, (i) 中西医结合 integrative medicine, (j) 循证中医 + 临床流行病学 evidence-based TCM + 现代研究, (k) 中医诊所备案 / 中医师资格 / NATCM 监管 / 药典 / GMP regulatory framework, (l) 国家级名老中医 学术继承人 项目 transmission program; NOT 道家修炼 / 风水 / 算命八字 (那是 玄学不是 中医), NOT 中医养生科普 (是 衍生 不是 临床主体), NOT 中医美容 (是 商业化分支), NOT 民族医学 (藏蒙维傣 是 平行体系 不在本 skill 主线 — 仅作 边界标注).: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on Traditional Chinese Medicine (TCM) clinical practice — the cognitive operating system of practicing TCM physicians covering (a) 经典理论 (阴阳/五行/脏腑/气血津液/经络/六淫/七情/六经/卫气营血/三焦) classical theory, (b) 四诊 (望闻问切) clinical observation/inquiry/pulse + 八纲 (阴阳/表里/寒热/虚实) syndrome differentiation, (c) 治法 (汗吐下和温清消补 + 扶正祛邪) therapeutic principles, (d) 方剂学 (经方 时方 验方) formula science, (e) 中药学 (四气五味/归经/七情/炮制/配伍禁忌) materia medica, (f) 针灸学 (经络穴位/手法/灸法/电针) acupuncture+moxibustion, (g) 推拿按摩 tuina massage, (h) 中医各科 (内/外/妇/儿/骨伤/皮肤/眼/耳鼻喉/肛肠/老年/急症) clinical specialties, (i) 中西医结合 integrative medicine, (j) 循证中医 + 临床流行病学 evidence-based TCM + 现代研究, (k) 中医诊所备案 / 中医师资格 / NATCM 监管 / 药典 / GMP regulatory framework, (l) 国家级名老中医 学术继承人 项目 transmission program; NOT 道家修炼 / 风水 / 算命八字 (那是 玄学不是 中医), NOT 中医养生科普 (是 衍生 不是 临床主体), NOT 中医美容 (是 商业化分支), NOT 民族医学 (藏蒙维傣 是 平行体系 不在本 skill 主线 — 仅作 边界标注). problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「中医」「中医学」「中医药」「中医诊疗」「中医临床」
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill whenever you are reasoning about large-scale scientific projects, genomics, bioethics, data infrastructure, or long-term medical translation. Eric S. Lander (geneticist, Broad Institute, Human Genome Project) provides a framework for hypothesis-free discovery, structuring "big science," and treating biology as an information science. Reach for this when the user is discussing open science, collaborative ecosystems, CRISPR/gene editing ethics, managing massive datasets, or setting realistic timelines for technological breakthroughs. Apply his principles to avoid the "lone genius" myth, prevent overpromising, and build foundational infrastructure that serves the broader community.
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Systematic literature review methodology for social science research. Use when conducting systematic reviews, research synthesis, meta-analyses, scoping reviews, or comprehensive literature searches across economics, political science, sociology, education, public health, and development. Produces structured notebook cells with search strategy, evidence table, thematic synthesis, and gap analysis.
日本語の概要は準備中です。原文の説明を表示しています。
Expert-level planetary science covering solar system formation, planetary interiors, atmospheres, surface processes, astrobiology, and planetary exploration missions.
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Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
日本語の概要は準備中です。原文の説明を表示しています。
将 Web of Science 数据库导出的纯文本格式（包含 AU, TI, SO 等标签）转换为标准的参考文献引用格式。
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' 'consumer behavior,' 'anchoring,' 'social proof,' 'scarcity,' 'loss aversion,' 'framing,' or 'nudge.' Use this whenever someone wants to understand or leverage how people think and make decisions in a marketing context. For applying psychology to specific pages, see cro; for pricing tactics, see pricing; for copy framing, see copywriting.
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Discovers and evaluates scientific datasets, models, methodology posts, and Spaces through the Hugging Science catalog. Used when selecting scientific ML resources in biology, chemistry, genomics, materials, climate, physics, astronomy, medicine, mathematics, protein design, single-cell analysis, or PDE modeling, and when checking their actual datasets, Transformers, native-runtime, Inference Providers, or Gradio interfaces.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' or 'consumer behavior.' This skill provides 70+ mental models organized for marketing application.
日本語の概要は準備中です。原文の説明を表示しています。