[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skills:stats":3,"skills:sce6":8,"skills:pro6":55,"skills:creators9":100,"skills:all:stars:10596:":195},{"skillCount":4,"professionCount":5,"scenarioCount":6,"creatorCount":7},196852,11,7,1926,[9,20,27,34,41,48],{"categoryNo":10,"taxonomyType":11,"taxonomyTypeDesc":12,"categoryName":13,"categoryNameEn":14,"description":15,"level":16,"skillCount":17,"parentNo":18,"parentName":18,"children":19},"01JBSEEDCAT000000000000022","SCENARIO","使用场景","智能体与自动化","Agents & Automation","Skill、MCP、智能体与工作流自动化",1,39458,null,[],{"categoryNo":21,"taxonomyType":11,"taxonomyTypeDesc":12,"categoryName":22,"categoryNameEn":23,"description":24,"level":16,"skillCount":25,"parentNo":18,"parentName":18,"children":26},"01JBSEEDCAT000000000000006","软件开发","Software Development","编码、测试、部署等软件研发任务",26531,[],{"categoryNo":28,"taxonomyType":11,"taxonomyTypeDesc":12,"categoryName":29,"categoryNameEn":30,"description":31,"level":16,"skillCount":32,"parentNo":18,"parentName":18,"children":33},"01JBSEEDCAT000000000000014","设计创意","Design & Creative","视觉设计、品牌与多媒体创作",13569,[],{"categoryNo":35,"taxonomyType":11,"taxonomyTypeDesc":12,"categoryName":36,"categoryNameEn":37,"description":38,"level":16,"skillCount":39,"parentNo":18,"parentName":18,"children":40},"01JBSEEDCAT000000000000001","办公效率","Office Productivity","日常办公文档、表格、演示与沟通类任务",6289,[],{"categoryNo":42,"taxonomyType":11,"taxonomyTypeDesc":12,"categoryName":43,"categoryNameEn":44,"description":45,"level":16,"skillCount":46,"parentNo":18,"parentName":18,"children":47},"01JBSEEDCAT000000000000017","内容创作","Content Creation","写作、文案与营销内容生产",6029,[],{"categoryNo":49,"taxonomyType":11,"taxonomyTypeDesc":12,"categoryName":50,"categoryNameEn":51,"description":52,"level":16,"skillCount":53,"parentNo":18,"parentName":18,"children":54},"01JBSEEDCAT000000000000020","研究与学习","Research & Learning","资料检索、知识整理与学习辅导",5531,[],[56,65,72,79,86,93],{"categoryNo":57,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":60,"categoryNameEn":61,"description":62,"level":16,"skillCount":63,"parentNo":18,"parentName":18,"children":64},"01JBSEEDCAT000000000000030","PROFESSION","适用职业","开发工程师","Software Engineer","从事软件编码、测试与运维的工程师",13274,[],{"categoryNo":66,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":67,"categoryNameEn":68,"description":69,"level":16,"skillCount":70,"parentNo":18,"parentName":18,"children":71},"01JBSEEDCAT000000000000032","设计师","Designer","视觉、交互与品牌设计人员",7775,[],{"categoryNo":73,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":74,"categoryNameEn":75,"description":76,"level":16,"skillCount":77,"parentNo":18,"parentName":18,"children":78},"01JBSEEDCAT000000000000033","数据分析师","Data Analyst","数据分析、报表与商业智能人员",4988,[],{"categoryNo":80,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":81,"categoryNameEn":82,"description":83,"level":16,"skillCount":84,"parentNo":18,"parentName":18,"children":85},"01JBSEEDCAT000000000000036","内容创作者","Content Creator","作者、编辑与自媒体创作者",3940,[],{"categoryNo":87,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":88,"categoryNameEn":89,"description":90,"level":16,"skillCount":91,"parentNo":18,"parentName":18,"children":92},"01JBSEEDCAT000000000000035","市场营销","Marketer","市场推广、增长与品牌运营人员",3446,[],{"categoryNo":94,"taxonomyType":58,"taxonomyTypeDesc":59,"categoryName":95,"categoryNameEn":96,"description":97,"level":16,"skillCount":98,"parentNo":18,"parentName":18,"children":99},"01JBSEEDCAT000000000000037","律师与法务","Legal","合同、合规与法律事务人员",3316,[],{"records":101,"total":7,"current":16,"size":194},[102,114,123,133,143,153,163,172,182],{"accountNo":103,"login":104,"displayName":105,"avatarUrl":106,"accountType":107,"accountTypeDesc":108,"profileDescription":109,"skillCount":110,"repoCount":111,"professionCount":5,"scenarioCount":6,"totalStars":112,"updatedAt":113},"01M698VYDXZ6JW5WH3CRV650R8","microsoft","Microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","ORGANIZATION","组织","Open source projects and samples from Microsoft",4160,229,828772,"2026-11-13 04:10:52",{"accountNo":115,"login":116,"displayName":116,"avatarUrl":117,"accountType":107,"accountTypeDesc":108,"profileDescription":118,"skillCount":119,"repoCount":120,"professionCount":6,"scenarioCount":6,"totalStars":121,"updatedAt":122},"01M698P3FSAZ6B4R928ZF19KPT","openclaw","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F252820863?v=4","Your personal, open source AI assistant.",362,32,437711,"2026-11-13 03:02:05",{"accountNo":124,"login":125,"displayName":126,"avatarUrl":127,"accountType":107,"accountTypeDesc":108,"profileDescription":18,"skillCount":128,"repoCount":129,"professionCount":6,"scenarioCount":130,"totalStars":131,"updatedAt":132},"01M6AC29YGCR4S2NTJFV0G8B81","openai","OpenAI","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F14957082?v=4",171,23,6,342695,"2026-11-13 04:03:41",{"accountNo":134,"login":135,"displayName":136,"avatarUrl":137,"accountType":107,"accountTypeDesc":108,"profileDescription":18,"skillCount":138,"repoCount":139,"professionCount":140,"scenarioCount":6,"totalStars":141,"updatedAt":142},"01M6AC83E6K4FDKK7HZ8WNMQKE","apache","The Apache Software Foundation","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F47359?v=4",420,75,8,298176,"2026-11-13 03:14:28",{"accountNo":144,"login":145,"displayName":146,"avatarUrl":147,"accountType":107,"accountTypeDesc":108,"profileDescription":148,"skillCount":149,"repoCount":150,"professionCount":5,"scenarioCount":6,"totalStars":151,"updatedAt":152},"01M698VYEFDM0VJBZDYYJ2T83S","google","Google","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F1342004?v=4","Google ❤️ Open Source",535,48,242366,"2026-11-13 04:17:09",{"accountNo":154,"login":155,"displayName":156,"avatarUrl":157,"accountType":107,"accountTypeDesc":108,"profileDescription":158,"skillCount":159,"repoCount":160,"professionCount":5,"scenarioCount":6,"totalStars":161,"updatedAt":162},"01M6AC83DS133TPXFSP1DHNCC6","github","GitHub","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F9919?v=4","How people build software.",940,28,238441,"2026-11-13 03:57:35",{"accountNo":164,"login":165,"displayName":166,"avatarUrl":167,"accountType":107,"accountTypeDesc":108,"profileDescription":18,"skillCount":168,"repoCount":169,"professionCount":5,"scenarioCount":6,"totalStars":170,"updatedAt":171},"01M697XGDPXJAVQ8391V2BCYTE","anthropics","Anthropic","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F76263028?v=4",674,17,231826,"2026-11-13 04:18:26",{"accountNo":173,"login":174,"displayName":175,"avatarUrl":176,"accountType":107,"accountTypeDesc":108,"profileDescription":18,"skillCount":177,"repoCount":178,"professionCount":179,"scenarioCount":6,"totalStars":180,"updatedAt":181},"01M6AC83EPDGBFN19MWYRREJD0","Significant-Gravitas","AutoGPT","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130738209?v=4",86,2,10,188014,"2026-11-13 02:38:59",{"accountNo":183,"login":184,"displayName":185,"avatarUrl":186,"accountType":187,"accountTypeDesc":188,"profileDescription":189,"skillCount":190,"repoCount":191,"professionCount":130,"scenarioCount":6,"totalStars":192,"updatedAt":193},"01M6DJCCDDG53MTYYRTXAXFG17","garrytan","Garry Tan","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F19957?v=4","USER","个人作者","Writes software, dreams. ",324,3,174614,"2026-11-13 04:05:07",9,{"records":196,"total":4,"current":541,"size":542},[197,227,257,271,284,300,328,346,370,381,406,420,436,453,475,494,504,528],{"skillNo":198,"name":199,"nameZh":18,"description":200,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":209,"categories":210,"keywords":211,"publishedAt":226},"01M6DARJ70MKAP2EADXWJV30PH","tooluniverse-gwas-study-explorer","Compare GWAS studies, perform meta-analyses, and assess replication across cohorts. Integrates NHGRI-EBI GWAS Catalog and Open Targets Genetics to compare study designs, effect sizes, ancestry diversity, and heterogeneity statistics. Use when comparing GWAS studies for a trait, performing meta-analysis of genetic loci, assessing replication across cohorts, or exploring the genetic architecture of complex diseases.","Prekzursil\u002Fagent-skills-toolchain","Prekzursil","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F54636077?v=4","01M6DACZ1PCQHD99SCR1YXG28B","Andrei Mihai Visalon","01M6DACZ670WZF535V3WYYSS4Z",0,"MIT","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-gwas-study-explorer\u002FSKILL.md",[],[212,213,214,215,216,217,218,219,220,221,222,223,224,225],"explorer","study","tooluniverse gwas study explorer","architecture","Meta","analysis","open","effect","catalog","use","across","diversity","genetics","statistics","2026-11-10 10:12:30",{"skillNo":228,"name":229,"nameZh":18,"description":230,"descriptionZh":18,"repositoryFullName":231,"ownerLogin":232,"ownerAvatarUrl":233,"ownerAccountNo":234,"ownerDisplayName":18,"repositoryNo":235,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":236,"categories":237,"keywords":241,"publishedAt":226},"01M6DARFCNQV3ED76AR72ZBVRJ","bws-cli-skill","Use when working with Bitwarden Secrets Manager CLI (bws) to run commands with injected secrets, manage secret-manager environment variables, or explain bws usage. Essential for wrapping processes with `bws run --project-id ${BWS_TZEHOUSE_ID_PROD or BWS_TZEHOUSE_ID_DEV} -- {command}`.","tzeusy-org\u002Fai-bootstrap","tzeusy-org","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F141543652?v=4","01M6DAM1AP09H27BYGFY9QCNPB","01M6DAM1F4R187EK11XDN9JZKH","https:\u002F\u002Fgithub.com\u002Ftzeusy-org\u002Fai-bootstrap\u002Fblob\u002Fmain\u002Fskills\u002Fbws-cli-skill\u002FSKILL.md",[238],{"categoryNo":239,"categoryName":240,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000023","Skill与智能体开发",[242,243,244,245,246,247,248,249,221,250,251,252,253,254,255,256],"cli","bws cli skill","run","dev","secrets","explain","command","environment","manage","bitwarden","active","project","commands","essential","id",{"skillNo":258,"name":259,"nameZh":18,"description":260,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":261,"categories":262,"keywords":263,"publishedAt":226},"01M6DARF4DE1PEJM9QH2ZGJFGC","tooluniverse-gwas-snp-interpretation","Interpret genetic variants (SNPs) from GWAS studies by aggregating evidence from multiple databases (GWAS Catalog, Open Targets Genetics, ClinVar). Retrieves variant annotations, GWAS trait associations, fine-mapping evidence, locus-to-gene predictions, and clinical significance. Use when asked to interpret a SNP by rsID, find disease associations for a variant, assess clinical significance, or answer questions like \"What diseases is rs429358 associated with?\" or \"Interpret rs7903146\".","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-gwas-snp-interpretation\u002FSKILL.md",[],[264,265,218,266,267,220,221,268,269,224,270],"interpretation","tooluniverse gwas snp interpretation","annotations","find","evidence","databases","clinical",{"skillNo":272,"name":273,"nameZh":18,"description":274,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":275,"categories":276,"keywords":277,"publishedAt":226},"01M6DARC800ZRVB3T4HJYKFDQ8","tooluniverse-gwas-finemapping","Identify and prioritize causal variants at GWAS loci using statistical fine-mapping and locus-to-gene predictions. Computes posterior probabilities for causal variants, links variants to genes via L2G predictions, annotates functional consequences, and suggests validation strategies. Use when asked to fine-map GWAS loci, prioritize causal variants, identify credible sets, or link GWAS signals to causal genes.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-gwas-finemapping\u002FSKILL.md",[],[278,279,280,221,281,282,283],"tooluniverse gwas finemapping","validation","prioritize","map","signals","strategies",{"skillNo":285,"name":286,"nameZh":18,"description":287,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":288,"categories":289,"keywords":290,"publishedAt":226},"01M6DAR8Z01QNZ77BB0B6KCRJ9","tooluniverse-gwas-drug-discovery","Transform GWAS signals into actionable drug targets and repurposing opportunities. Performs locus-to-gene mapping, target druggability assessment, existing drug identification, safety profile evaluation, and clinical trial matching. Use when discovering drug targets from GWAS data, finding drug repurposing opportunities from genetic associations, or translating GWAS findings into therapeutic leads.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-gwas-drug-discovery\u002FSKILL.md",[],[291,292,293,294,295,296,297,221,282,298,299,270],"discovery","tooluniverse gwas drug discovery","assessment","Evaluation","data","Safety","profile","gene mapping","matching",{"skillNo":301,"name":302,"nameZh":18,"description":303,"descriptionZh":18,"repositoryFullName":231,"ownerLogin":232,"ownerAvatarUrl":233,"ownerAccountNo":234,"ownerDisplayName":18,"repositoryNo":235,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":304,"categories":305,"keywords":311,"publishedAt":226},"01M6DAR806BXF23TM5H7MPBW8M","writing-agents","Guide for creating effective LLM subagent prompts and personas. This skill should be used when writing, reviewing, or improving agent definitions for Claude Code or similar multi-agent systems. Covers YAML frontmatter, system prompt structure, tool selection, and common pitfalls.","https:\u002F\u002Fgithub.com\u002Ftzeusy-org\u002Fai-bootstrap\u002Fblob\u002Fmain\u002Fskills\u002Farchive\u002Fwriting-agents\u002FSKILL.md",[306,309,310],{"categoryNo":307,"categoryName":308,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":239,"categoryName":240,"taxonomyType":11,"taxonomyTypeDesc":12},{"categoryNo":80,"categoryName":81,"taxonomyType":58,"taxonomyTypeDesc":59},[312,313,314,315,316,317,318,319,320,321,322,323,324,325,326,327],"writing","writing agents","code","yaml","subagent","system","tool","multi-agent","common","prompt","guide","prompts","selection","personas","structure","systems",{"skillNo":329,"name":330,"nameZh":18,"description":331,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":332,"categories":333,"keywords":337,"publishedAt":226},"01M6DAR5VY1NBAGCEG8WT6HST3","tooluniverse-gpcr-structural-pharmacology","Research GPCR receptors, antibody structures, and protein interface analysis using GPCRdb, SAbDab, and PDBePISA. Retrieves receptor families, known ligands (agonists\u002Fantagonists\u002Fbiased), mutations, crystal\u002Fcryo-EM structures, antibody CDR annotations, and protein-protein interface geometry. Use when asked about GPCR drug targets, receptor-ligand interactions, antibody structural data, or protein assembly interfaces.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-gpcr-structural-pharmacology\u002FSKILL.md",[334],{"categoryNo":335,"categoryName":336,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000021","资料检索与研究",[338,339,340,295,341,217,266,221,342,343,344,345],"structural","tooluniverse gpcr structural pharmacology","research","CDR","assembly","mutations","geometry","crystal",{"skillNo":347,"name":348,"nameZh":18,"description":349,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":350,"categories":351,"keywords":355,"publishedAt":226},"01M6DAR2DPMQBYGCT8WMM4WMS3","tooluniverse-gene-enrichment","Perform comprehensive gene enrichment and pathway analysis using gseapy (ORA and GSEA), PANTHER, STRING, Reactome, and 40+ ToolUniverse tools. Supports GO enrichment (BP, MF, CC), KEGG, Reactome, WikiPathways, MSigDB Hallmark, and 220+ Enrichr libraries. Handles multiple ID types (gene symbols, Ensembl, Entrez, UniProt), multiple organisms (human, mouse, rat, fly, worm, yeast), customizable backgrounds, and multiple testing correction (BH, Bonferroni). Use when users ask about gene enrichment, pathway analysis, GO term enrichment, KEGG pathway analysis, GSEA, over-representation analysis, functional annotation, or gene set analysis.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-gene-enrichment\u002FSKILL.md",[352],{"categoryNo":353,"categoryName":354,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000008","测试与质量",[356,357,358,359,360,361,362,363,364,217,365,366,367,221,368,369,256],"enrichment","tooluniverse gene enrichment","testing","go","libraries","SET","Tools","rat","worm","fly","hallmark","ask","cc","human",{"skillNo":371,"name":372,"nameZh":18,"description":373,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":374,"categories":375,"keywords":376,"publishedAt":226},"01M6DAQZFMX264T62XDS78XYB0","tooluniverse-gene-disease-association","Find and compare gene-disease associations across multiple databases (DisGeNET, OpenTargets, Monarch Initiative, OMIM, GenCC, Orphanet, ClinVar). Produces a unified evidence table with confidence levels and cross-database concordance. Use when users ask about gene-disease links, disease genes, genetic basis of disease, or want to compare association evidence across sources.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-gene-disease-association\u002FSKILL.md",[],[377,378,379,267,367,221,268,269,380,222],"tooluniverse gene disease association","database","table","evidence table",{"skillNo":382,"name":383,"nameZh":18,"description":384,"descriptionZh":18,"repositoryFullName":231,"ownerLogin":232,"ownerAvatarUrl":233,"ownerAccountNo":234,"ownerDisplayName":18,"repositoryNo":235,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":385,"categories":386,"keywords":390,"publishedAt":226},"01M6DAQY0RARKE8NJZR5Z2CGE1","youtube-downloader","Download YouTube videos with customizable quality and format options. Use this skill when the user asks to download, save, or grab YouTube videos. Supports various quality settings (best, 1080p, 720p, 480p, 360p), multiple formats (mp4, webm, mkv), and audio-only downloads as MP3.","https:\u002F\u002Fgithub.com\u002Ftzeusy-org\u002Fai-bootstrap\u002Fblob\u002Fmain\u002Fskills\u002Farchive\u002Fvideo-downloader\u002FSKILL.md",[387],{"categoryNo":388,"categoryName":389,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000016","图像与多媒体",[391,392,393,394,395,396,397,398,399,400,401,221,402,403,404,405],"youtube downloader","youtube","downloads","Audio","save","format","download","mp4","quality","settings","user","only","mp3","options","as",{"skillNo":407,"name":408,"nameZh":18,"description":409,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":410,"categories":411,"keywords":412,"publishedAt":226},"01M6DAQWSZ6Y5XFSK1125KKTNF","tooluniverse-functional-genomics-screens","Interpret results from CRISPR\u002FshRNA genetic screens using DepMap essentiality data, constraint scores, pathway enrichment, protein networks, druggability assessment, and clinical evidence. Use for screen hit validation, gene essentiality analysis, DepMap exploration, functional genomics interpretation, and screen-to-target prioritization.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-functional-genomics-screens\u002FSKILL.md",[],[413,414,264,293,279,295,356,415,217,416,417,221,268,418,419,270],"genomics","tooluniverse functional genomics screens","networks","prioritization","results","exploration","depmap",{"skillNo":421,"name":422,"nameZh":18,"description":423,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":424,"categories":425,"keywords":427,"publishedAt":226},"01M6DAQT23R8RSPETJFKSTB28H","tooluniverse-expression-data-retrieval","Retrieves gene expression and omics datasets from ArrayExpress and BioStudies with gene disambiguation, experiment quality assessment, and structured reports. Creates comprehensive dataset profiles with metadata, sample information, and download links. Use when users need expression data, omics datasets, or mention ArrayExpress (E-MTAB, E-GEOD) or BioStudies (S-BSST) accessions.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-expression-data-retrieval\u002FSKILL.md",[426],{"categoryNo":73,"categoryName":74,"taxonomyType":58,"taxonomyTypeDesc":59},[295,428,293,429,397,399,221,430,431,432,433,434,435],"tooluniverse expression data retrieval","metadata","experiment","reports","datasets","structured","sample","gene expression",{"skillNo":437,"name":438,"nameZh":18,"description":439,"descriptionZh":18,"repositoryFullName":231,"ownerLogin":232,"ownerAvatarUrl":233,"ownerAccountNo":234,"ownerDisplayName":18,"repositoryNo":235,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":440,"categories":441,"keywords":442,"publishedAt":226},"01M6DAQPT7HBG3QV768BZ68Z22","training-curriculum","Use when you need to inspect a target repository and generate a repo-grounded prerequisite curriculum in `curriculum\u002F` that teaches the fundamental technical concepts someone must know before the codebase will make sense or be safe to change.","https:\u002F\u002Fgithub.com\u002Ftzeusy-org\u002Fai-bootstrap\u002Fblob\u002Fmain\u002Fskills\u002Farchive\u002Ftraining-curriculum\u002FSKILL.md",[],[443,444,445,446,447,448,125,449,450,451,221,252,452],"training","training curriculum","safe","codex","change","generate","repository","technical","repo","openai codex",{"skillNo":454,"name":455,"nameZh":18,"description":456,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":457,"categories":458,"keywords":459,"publishedAt":226},"01M6DAQPHWTVA75BNYXQZMWJK2","tooluniverse-epigenomics","Production-ready genomics and epigenomics data processing for BixBench questions. Handles methylation array analysis (CpG filtering, differential methylation, age-related CpG detection, chromosome-level density), ChIP-seq peak analysis (peak calling, motif enrichment, coverage stats), ATAC-seq chromatin accessibility, multi-omics integration (expression + methylation correlation), and genome-wide statistics. Pure Python computation (pandas, scipy, numpy, pysam, statsmodels) plus ToolUniverse annotation tools (Ensembl, ENCODE, SCREEN, JASPAR, ReMap, RegulomeDB, ChIPAtlas). Supports BED, BigWig, methylation beta-value matrices, Illumina manifest files, and multi-sample clinical data. Use when processing methylation data, ChIP-seq peaks, ATAC-seq signals, or answering questions about CpG sites, differential methylation, chromatin accessibility, histone marks, or epigenomic statistics.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-epigenomics\u002FSKILL.md",[],[460,461,462,463,464,465,217,466,467,221,468,469,470,471,472,434,225,270,473,474],"tooluniverse epigenomics","python","pandas","beta","stats","manifest","coverage","filtering","ready","files","calling","numpy","scipy","age","atac",{"skillNo":476,"name":477,"nameZh":18,"description":478,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":479,"categories":480,"keywords":482,"publishedAt":226},"01M6DAQKDTA7WES0E3PA564VBH","tooluniverse-epigenomics-chromatin","Epigenomics and chromatin accessibility research -- histone modification ChIP-seq data from ENCODE, CTCF binding and chromatin architecture, eQTL analysis connecting variants to gene regulation, gene expression correlation with chromatin marks, regulatory element identification via SCREEN\u002FUCSC cCREs, transcription factor binding motifs via JASPAR\u002FReMap, and variant regulatory scoring via RegulomeDB. Use when users ask about histone marks, chromatin states, CTCF binding, eQTLs, cis-regulatory elements, enhancer\u002Fpromoter annotation, or chromatin accessibility in specific cell types.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-epigenomics-chromatin\u002FSKILL.md",[481],{"categoryNo":335,"categoryName":336,"taxonomyType":11,"taxonomyTypeDesc":12},[483,340,484,215,485,295,486,217,367,221,487,488,489,490,435,491,492,474,493],"tooluniverse epigenomics chromatin","accessibility","state","correlation","regulatory","cis","transcription","scoring","cell","elements","factor",{"skillNo":495,"name":496,"nameZh":18,"description":497,"descriptionZh":18,"repositoryFullName":231,"ownerLogin":232,"ownerAvatarUrl":233,"ownerAccountNo":234,"ownerDisplayName":18,"repositoryNo":235,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":498,"categories":499,"keywords":501,"publishedAt":226},"01M6DAQHE29QD2797J90H0Y29F","template-skill","Replace with description of the skill and when Claude should use it.","https:\u002F\u002Fgithub.com\u002Ftzeusy-org\u002Fai-bootstrap\u002Fblob\u002Fmain\u002Fskills\u002Farchive\u002Ftemplate\u002FSKILL.md",[500],{"categoryNo":239,"categoryName":240,"taxonomyType":11,"taxonomyTypeDesc":12},[502,503,221],"template skill","template",{"skillNo":505,"name":506,"nameZh":18,"description":507,"descriptionZh":18,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":508,"categories":509,"keywords":514,"publishedAt":226},"01M6DAQFMY78AWZ21KRN80CCAK","tooluniverse-epidemiological-analysis","End-to-end epidemiological data analysis — from research question to statistical report. Covers study design assessment, dataset discovery and download, data wrangling, confounder adjustment, regression modeling, sensitivity analysis, visualization, and biological interpretation. Integrates ToolUniverse tools for dataset discovery, literature search, and biological context with Python code execution for data analysis. Use whenever users ask to analyze health data, study disease risk factors, assess exposure-outcome relationships, or conduct observational epidemiology. Also use when users want to run regression on clinical\u002Fsurvey data, calculate odds ratios or hazard ratios from a dataset, adjust for confounders, or produce a Table 1. If the task involves downloading a health dataset and running statistical analysis on it, this is the right skill.","https:\u002F\u002Fgithub.com\u002FPrekzursil\u002Fagent-skills-toolchain\u002Fblob\u002Fmain\u002F.agents\u002Flibrary\u002Fskills\u002Ftooluniverse-epidemiological-analysis\u002FSKILL.md",[510,513],{"categoryNo":511,"categoryName":512,"taxonomyType":11,"taxonomyTypeDesc":12},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":335,"categoryName":336,"taxonomyType":11,"taxonomyTypeDesc":12},[217,515,516,461,517,264,293,518,519,520,521,291,522,523,524,213,525,526,527,270],"tooluniverse epidemiological analysis","design","sensitivity analysis","visualization","search","execution","risk","regression","question","survey","sensitivity","adjust","end",{"skillNo":529,"name":530,"nameZh":18,"description":531,"descriptionZh":18,"repositoryFullName":231,"ownerLogin":232,"ownerAvatarUrl":233,"ownerAccountNo":234,"ownerDisplayName":18,"repositoryNo":235,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":18,"sourceHtmlUrl":532,"categories":533,"keywords":537,"publishedAt":226},"01M6DAQEN4J4JW5VRMD07HGVMA","tailored-resume-generator","Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances","https:\u002F\u002Fgithub.com\u002Ftzeusy-org\u002Fai-bootstrap\u002Fblob\u002Fmain\u002Fskills\u002Farchive\u002Ftailored-resume-generator\u002FSKILL.md",[534],{"categoryNo":535,"categoryName":536,"taxonomyType":58,"taxonomyTypeDesc":59},"01JBSEEDCAT000000000000038","人力资源",[538,539,540],"tailored resume generator","resume","interview",10596,18]