[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6DM4NJH49T6BPE7MT74SBC9":3,"skill-same:01M6DM4NJH49T6BPE7MT74SBC9":58},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":25,"linkOnly":26,"markdownContent":27,"markdownBody":28,"frontMatter":29,"refName":36,"commitSha":37,"skillDirectory":38,"forksCount":39,"repositoryHtmlUrl":40,"repositoryHomepageUrl":6,"ownerHtmlUrl":41,"ownerBlogUrl":6,"ownerDescription":42,"updatedAt":43,"install":44,"resources":57},"01M6DM4NJH49T6BPE7MT74SBC9","variant-pharmacogenomics",null,"Query PharmGKB (clinPGx) for pharmacogenomic clinical annotations — how a variant affects drug response, dosing, and adverse reactions.","InternScience\u002FDrClaw","InternScience","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F154449623?v=4","01M6DHY1ZF02QASNAVMNPT7NP6","Intern Science","01M6DHY2523FY56Q5572NKAAD0",172,"MIT","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fscience\u002Fdrug\u002Fvariant-pharmacogenomics\u002FSKILL.md",[],[19,20,21,22,23,24],"variant pharmacogenomics","how","annotations","query","reactions","clinical","2026-11-10 10:12:30",false,"---\nname: variant-pharmacogenomics\ndescription: Query PharmGKB (clinPGx) for pharmacogenomic clinical annotations — how\n  a variant affects drug response, dosing, and adverse reactions.\nlicense: MIT license\nmetadata:\n  skill-author: PJLab\ni18n:\n  zh:\n    description: 查询变异对药物反应的影响。\n---\n\n# PharmGKB (clinPGx) — Pharmacogenomic Annotations\n\n## Usage\n\n### Tool Description\n\n```tex\nQuery PharmGKB clinical annotations API to find drug-gene-variant interactions.\nDatabase: PharmGKB \u002F clinPGx (https:\u002F\u002Fwww.pharmgkb.org\u002F)\nAPI: GET https:\u002F\u002Fapi.clinpgx.org\u002Fv1\u002Fdata\u002FclinicalAnnotation?location.fingerprint={rsid}&view=base\nArgs:\n    rs_id (str): dbSNP rsID (e.g. \"rs7412\")\nReturn:\n    Clinical annotations: related drugs (chemicals), evidence level (1A\u002F1B\u002F2A\u002F2B\u002F3\u002F4),\n    related diseases, gene (APOE etc.), phenotype categories (efficacy\u002Ftoxicity\u002Fdosage\u002FPK),\n    related guidelines and FDA labels.\n\nReturn Fields Explanation:\n    - relatedChemicals: 关联的药物\u002F化合物名称和 PharmGKB ID\n    - levelOfEvidence.term: 证据级别 (1A=最强, 有CPIC\u002FDPWG指南; 4=最弱, 个案报告)\n    - location.genes: 变异所在基因\n    - relatedDiseases: 关联疾病\n    - types: 注释类型 (Efficacy=疗效, Toxicity=毒性, Dosage=剂量, PK=药代动力学)\n    - relatedGuidelines: 关联的用药指南 (CPIC, DPWG 等)\n    - relatedLabels: 关联的 FDA 药品标签\n```\n\n### Query Example\n\n```python\nimport requests\n\nrs_id = \"rs7412\"\nurl = f\"https:\u002F\u002Fapi.clinpgx.org\u002Fv1\u002Fdata\u002FclinicalAnnotation?location.fingerprint={rs_id}&view=base\"\nresp = requests.get(url, timeout=30).json()\n\nif isinstance(resp, dict) and \"data\" in resp:\n    annotations = resp[\"data\"]\nelif isinstance(resp, list):\n    annotations = resp\nelse:\n    annotations = []\n\nprint(f\"[PharmGKB] {rs_id} 药物基因组注释数: {len(annotations)}\")\n\nfor i, ann in enumerate(annotations):\n    # 药物\n    drugs = [c.get(\"name\", \"\") for c in ann.get(\"relatedChemicals\", [])]\n    # 证据级别\n    evidence = ann.get(\"levelOfEvidence\", {}).get(\"term\", \"N\u002FA\")\n    # 基因\n    genes = [g.get(\"symbol\", \"\") for g in ann.get(\"location\", {}).get(\"genes\", [])]\n    # 疾病\n    diseases = [d.get(\"name\", \"\") for d in ann.get(\"relatedDiseases\", [])]\n    # 注释类型\n    ann_types = ann.get(\"types\", [])\n\n    print(f\"\\n  [{i+1}] 药物: {drugs}\")\n    print(f\"       证据级别: {evidence}\")\n    print(f\"       基因: {genes}\")\n    print(f\"       类型: {ann_types}\")\n    if diseases:\n        print(f\"       疾病: {diseases}\")\n```\n","# PharmGKB (clinPGx) — Pharmacogenomic Annotations\n\n## Usage\n\n### Tool Description\n\n```tex\nQuery PharmGKB clinical annotations API to find drug-gene-variant interactions.\nDatabase: PharmGKB \u002F clinPGx (https:\u002F\u002Fwww.pharmgkb.org\u002F)\nAPI: GET https:\u002F\u002Fapi.clinpgx.org\u002Fv1\u002Fdata\u002FclinicalAnnotation?location.fingerprint={rsid}&view=base\nArgs:\n    rs_id (str): dbSNP rsID (e.g. \"rs7412\")\nReturn:\n    Clinical annotations: related drugs (chemicals), evidence level (1A\u002F1B\u002F2A\u002F2B\u002F3\u002F4),\n    related diseases, gene (APOE etc.), phenotype categories (efficacy\u002Ftoxicity\u002Fdosage\u002FPK),\n    related guidelines and FDA labels.\n\nReturn Fields Explanation:\n    - relatedChemicals: 关联的药物\u002F化合物名称和 PharmGKB ID\n    - levelOfEvidence.term: 证据级别 (1A=最强, 有CPIC\u002FDPWG指南; 4=最弱, 个案报告)\n    - location.genes: 变异所在基因\n    - relatedDiseases: 关联疾病\n    - types: 注释类型 (Efficacy=疗效, Toxicity=毒性, Dosage=剂量, PK=药代动力学)\n    - relatedGuidelines: 关联的用药指南 (CPIC, DPWG 等)\n    - relatedLabels: 关联的 FDA 药品标签\n```\n\n### Query Example\n\n```python\nimport requests\n\nrs_id = \"rs7412\"\nurl = f\"https:\u002F\u002Fapi.clinpgx.org\u002Fv1\u002Fdata\u002FclinicalAnnotation?location.fingerprint={rs_id}&view=base\"\nresp = requests.get(url, timeout=30).json()\n\nif isinstance(resp, dict) and \"data\" in resp:\n    annotations = resp[\"data\"]\nelif isinstance(resp, list):\n    annotations = resp\nelse:\n    annotations = []\n\nprint(f\"[PharmGKB] {rs_id} 药物基因组注释数: {len(annotations)}\")\n\nfor i, ann in enumerate(annotations):\n    # 药物\n    drugs = [c.get(\"name\", \"\") for c in ann.get(\"relatedChemicals\", [])]\n    # 证据级别\n    evidence = ann.get(\"levelOfEvidence\", {}).get(\"term\", \"N\u002FA\")\n    # 基因\n    genes = [g.get(\"symbol\", \"\") for g in ann.get(\"location\", {}).get(\"genes\", [])]\n    # 疾病\n    diseases = [d.get(\"name\", \"\") for d in ann.get(\"relatedDiseases\", [])]\n    # 注释类型\n    ann_types = ann.get(\"types\", [])\n\n    print(f\"\\n  [{i+1}] 药物: {drugs}\")\n    print(f\"       证据级别: {evidence}\")\n    print(f\"       基因: {genes}\")\n    print(f\"       类型: {ann_types}\")\n    if diseases:\n        print(f\"       疾病: {diseases}\")\n```\n",{"i18n":30,"name":5,"license":33,"metadata":34,"description":7},{"zh":31},{"description":32},"查询变异对药物反应的影响。","MIT license",{"skill-author":35},"PJLab","main","4f96df0d9df0eae24a992afabe08edec5fc575f0","drclaw\u002Flocal_skill_hub\u002Fscience\u002Fdrug\u002Fvariant-pharmacogenomics",10,"https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw","https:\u002F\u002Fgithub.com\u002FInternScience","Shanghai Artificial Intelligence Laboratory","2026-03-20 17:06:10",{"source":8,"skillName":5,"commands":45,"prompt":55,"zipAvailable":56},[46,49,52],{"tool":47,"command":48},"npx","npx skills add InternScience\u002FDrClaw --skill variant-pharmacogenomics",{"tool":50,"command":51},"bunx","bunx skills add InternScience\u002FDrClaw --skill variant-pharmacogenomics",{"tool":53,"command":54},"pnpm","pnpm dlx skills add InternScience\u002FDrClaw --skill variant-pharmacogenomics","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fscience\u002Fdrug\u002Fvariant-pharmacogenomics\u002FSKILL.md",true,[],[59,96,119,137,155,169],{"skillNo":60,"name":61,"nameZh":6,"description":62,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":63,"categories":64,"keywords":75,"publishedAt":25},"01M6DMQESTSBW8VJW03QWHMT85","scientific-critical-thinking","Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading frameworks (GRADE, Cochrane Risk of Bias), or teaching critical analysis. Best for understanding evidence quality, identifying flaws. For formal peer review writing use peer-review.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fthinking\u002Fscientific-critical-thinking\u002FSKILL.md",[65,70],{"categoryNo":66,"categoryName":67,"taxonomyType":68,"taxonomyTypeDesc":69},"01JBSEEDCAT000000000000015","视觉设计","SCENARIO","使用场景",{"categoryNo":71,"categoryName":72,"taxonomyType":73,"taxonomyTypeDesc":74},"01JBSEEDCAT000000000000032","设计师","PROFESSION","适用职业",[76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95],"critical","scientific critical thinking","thinking","design","writing","review","risk","analysis","peer review","Bash","quality","read","write","edit","use","evidence","peer","frameworks","teaching","bias",{"skillNo":97,"name":98,"nameZh":6,"description":99,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":100,"categories":101,"keywords":102,"publishedAt":25},"01M6DMQ77Z121463E049G2DG8K","scientific-brainstorming","Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fthinking\u002Fscientific-brainstorming\u002FSKILL.md",[],[103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,90],"brainstorming","scientific brainstorming","research ideation","stage","connections","generation","exploration","do","planning","creative","ideation","research","sessions","data","hypothesis","open",{"skillNo":120,"name":121,"nameZh":6,"description":122,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":123,"categories":124,"keywords":131,"publishedAt":25},"01M6DMPV4AMCCTWARGPSFHDWJB","scientific-literature-search","Search scientific literature and research papers using FlowSearch to find relevant academic articles and publications.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fsearch\u002Fscientific-literature-search\u002FSKILL.md",[125,128],{"categoryNo":126,"categoryName":127,"taxonomyType":68,"taxonomyTypeDesc":69},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":129,"categoryName":130,"taxonomyType":68,"taxonomyTypeDesc":69},"01JBSEEDCAT000000000000023","Skill与智能体开发",[132,133,114,134,135,136],"search","scientific literature search","find","Academic","搜索",{"skillNo":138,"name":139,"nameZh":6,"description":140,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":141,"categories":142,"keywords":149,"publishedAt":25},"01M6DMPQJP8HVFV54V05D6K9HA","pubmed-article-search","Search PubMed database for scientific articles and publications to retrieve biomedical literature.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fsearch\u002Fpubmed-article-search\u002FSKILL.md",[143,146],{"categoryNo":144,"categoryName":145,"taxonomyType":68,"taxonomyTypeDesc":69},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":147,"categoryName":148,"taxonomyType":73,"taxonomyTypeDesc":74},"01JBSEEDCAT000000000000036","内容创作者",[150,151,132,136,152,153,154],"pubmed article search","article","database","pubmed database","biomedical",{"skillNo":156,"name":157,"nameZh":6,"description":158,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":159,"categories":160,"keywords":162,"publishedAt":25},"01M6DMPK4H3JQ185M97BRB9KQJ","biomedical-web-search","Search biomedical literature and web content using Tavily search engine for research and clinical information.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fsearch\u002Fbiomedical-web-search\u002FSKILL.md",[161],{"categoryNo":126,"categoryName":127,"taxonomyType":68,"taxonomyTypeDesc":69},[163,154,164,132,165,166,114,167,168,136,24],"biomedical web search","web search","web","tavily","content","engine",{"skillNo":170,"name":171,"nameZh":6,"description":172,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":173,"categories":174,"keywords":176,"publishedAt":25},"01M6DMNNJH9V1S5PQHZRX0N934","uniprot-protein-retrieval","Retrieve protein sequences and functional information from UniProt database by protein name, enabling protein analysis and bioinformatics workflows.","https:\u002F\u002Fgithub.com\u002FInternScience\u002FDrClaw\u002Fblob\u002Fmain\u002Fdrclaw\u002Flocal_skill_hub\u002Fscience\u002Fprotein\u002Funiprot-protein-retrieval\u002FSKILL.md",[175],{"categoryNo":129,"categoryName":130,"taxonomyType":68,"taxonomyTypeDesc":69},[177,152,83,178,179,180,181],"uniprot protein retrieval","uniprot database","bioinformatics","name","workflows"]