[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skills:pro6":3,"skills:sce6":50,"skills:creators9":95,"skills:stats":193,"skills:all:stars:158:":195},[4,15,22,29,36,43],{"categoryNo":5,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":8,"categoryNameEn":9,"description":10,"level":11,"skillCount":12,"parentNo":13,"parentName":13,"children":14},"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",1,13274,null,[],{"categoryNo":16,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":17,"categoryNameEn":18,"description":19,"level":11,"skillCount":20,"parentNo":13,"parentName":13,"children":21},"01JBSEEDCAT000000000000032","设计师","Designer","视觉、交互与品牌设计人员",7775,[],{"categoryNo":23,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":24,"categoryNameEn":25,"description":26,"level":11,"skillCount":27,"parentNo":13,"parentName":13,"children":28},"01JBSEEDCAT000000000000033","数据分析师","Data 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Learning","资料检索、知识整理与学习辅导",5531,[],{"records":96,"total":191,"current":11,"size":192},[97,111,120,130,140,150,160,169,179],{"accountNo":98,"login":99,"displayName":100,"avatarUrl":101,"accountType":102,"accountTypeDesc":103,"profileDescription":104,"skillCount":105,"repoCount":106,"professionCount":107,"scenarioCount":108,"totalStars":109,"updatedAt":110},"01M698VYDXZ6JW5WH3CRV650R8","microsoft","Microsoft","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6154722?v=4","ORGANIZATION","组织","Open source projects and samples from Microsoft",4160,229,11,7,828772,"2026-11-13 04:10:52",{"accountNo":112,"login":113,"displayName":113,"avatarUrl":114,"accountType":102,"accountTypeDesc":103,"profileDescription":115,"skillCount":116,"repoCount":117,"professionCount":108,"scenarioCount":108,"totalStars":118,"updatedAt":119},"01M698P3FSAZ6B4R928ZF19KPT","openclaw","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F252820863?v=4","Your personal, open source AI 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03:57:35",{"accountNo":161,"login":162,"displayName":163,"avatarUrl":164,"accountType":102,"accountTypeDesc":103,"profileDescription":13,"skillCount":165,"repoCount":166,"professionCount":107,"scenarioCount":108,"totalStars":167,"updatedAt":168},"01M697XGDPXJAVQ8391V2BCYTE","anthropics","Anthropic","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F76263028?v=4",674,17,231826,"2026-11-13 04:18:26",{"accountNo":170,"login":171,"displayName":172,"avatarUrl":173,"accountType":102,"accountTypeDesc":103,"profileDescription":13,"skillCount":174,"repoCount":175,"professionCount":176,"scenarioCount":108,"totalStars":177,"updatedAt":178},"01M6AC83EPDGBFN19MWYRREJD0","Significant-Gravitas","AutoGPT","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130738209?v=4",86,2,10,188014,"2026-11-13 02:38:59",{"accountNo":180,"login":181,"displayName":182,"avatarUrl":183,"accountType":184,"accountTypeDesc":185,"profileDescription":186,"skillCount":187,"repoCount":188,"professionCount":127,"scenarioCount":108,"totalStars":189,"updatedAt":190},"01M6DJCCDDG53MTYYRTXAXFG17","garrytan","Garry Tan","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F19957?v=4","USER","个人作者","Writes software, dreams. 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Search compounds by structure\u002Fproperties, retrieve bioactivity data (IC50, Ki), find inhibitors, perform SAR studies, for medicinal chemistry.","davila7\u002Fclaude-code-templates","davila7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6216945?v=4","01M6ADEWWFPS191NFM0Y1EX1JH","Daniel Avila","01M6ADJHGM78PHQRD3XZTFDVKK",33418,"MIT","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fchembl-database\u002FSKILL.md",[211,214],{"categoryNo":212,"categoryName":213,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000023","Skill与智能体开发",[218,219,220,221,222,223,224,225,226,227,228,229,230,231],"database","chembl database","chembl","search","data","discovery","find","properties","query","structure","drug discovery","sar","for","Molecules","2026-11-10 10:12:30",{"skillNo":234,"name":235,"nameZh":13,"description":236,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":237,"categories":238,"keywords":240,"publishedAt":232},"01M6AFAZCT72WBE8F9VS32QN5K","cellxgene-census","Query CZ CELLxGENE Census (61M+ cells). Filter by cell type\u002Ftissue\u002Fdisease, retrieve expression data, integrate with scanpy\u002FPyTorch, for population-scale single-cell analysis.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fcellxgene-census\u002FSKILL.md",[239],{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[241,242,222,243,244,245,226,246,247,248,249,250,251,252,253,230,254],"cellxgene census","pytorch","analysis","scanpy","integrate","cell","type","cz","expression","single-cell","filter","scale","with","single",{"skillNo":256,"name":257,"nameZh":13,"description":258,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":259,"categories":260,"keywords":264,"publishedAt":232},"01M6AFAW6HM0AJQ5Y81SZ7QRZD","brenda-database","Access BRENDA enzyme database via SOAP API. Retrieve kinetic parameters (Km, kcat), reaction equations, organism data, and substrate-specific enzyme information for biochemical research and metabolic pathway analysis.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fbrenda-database\u002FSKILL.md",[261,262,263],{"categoryNo":212,"categoryName":213,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[218,265,266,267,222,243,268,269,270,271,272,273,230,274],"brenda database","substrate","research","api","soap","access","pathway","via","information","kinetic",{"skillNo":276,"name":277,"nameZh":13,"description":278,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":279,"categories":280,"keywords":283,"publishedAt":232},"01M6AFARVC2Y60YX5N84NZW464","bioservices","Primary Python tool for 40+ bioinformatics services. Preferred for multi-database workflows: UniProt, KEGG, ChEMBL, PubChem, Reactome, QuickGO. Unified API for queries, ID mapping, pathway analysis. For direct REST control, use individual database skills (uniprot-database, kegg-database).","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fbioservices\u002FSKILL.md",[281,282],{"categoryNo":212,"categoryName":213,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[277,284,285,218,286,287,243,268,288,289,290,291,292,220,293,294,271,295,296,297,230],"python","workflows","services","REST","tool","direct","use","queries","id","KEGG","Reactome","mapping","multi","Unified API",{"skillNo":299,"name":300,"nameZh":13,"description":301,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":302,"categories":303,"keywords":309,"publishedAt":232},"01M6AFANXVSMSAKKVM9ADTRXC1","biorxiv-database","Efficient database search tool for bioRxiv preprint server. Use this skill when searching for life sciences preprints by keywords, authors, date ranges, or categories, retrieving paper metadata, downloading PDFs, or conducting literature reviews.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fbiorxiv-database\u002FSKILL.md",[304,305,308],{"categoryNo":212,"categoryName":213,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":306,"categoryName":307,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[218,310,221,311,312,288,290,313,314,315,316,317,318,230,319],"biorxiv database","metadata","server","life","paper","preprints","literature","categories","reviews","when",{"skillNo":321,"name":322,"nameZh":13,"description":323,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":324,"categories":325,"keywords":328,"publishedAt":232},"01M6AFAJHQZ872TJE6R3DDYPSM","biopython","Primary Python toolkit for molecular biology. Preferred for Python-based PubMed\u002FNCBI queries (Bio.Entrez), sequence manipulation, file parsing (FASTA, GenBank, FASTQ, PDB), advanced BLAST workflows, structures, phylogenetics. For quick BLAST, use gget. For direct REST API, use pubmed-database.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fbiopython\u002FSKILL.md",[326,327],{"categoryNo":212,"categoryName":213,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[322,284,285,329,218,330,287,331,268,332,289,333,334,335,336,337,338,339,340,341,342,343,344,345],"toolkit","file","gget","parsing","phylogenetics","molecular biology","molecular","pdb","Entrez","pubmed","biology","quick","advanced","sequence","FASTA","GenBank","NCBI",{"skillNo":347,"name":348,"nameZh":13,"description":349,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":350,"categories":351,"keywords":356,"publishedAt":232},"01M6AFAFJA9XPHNGVX425HX54C","biomni","Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction, GWAS interpretation, rare disease diagnosis, or lab protocol optimization. Leverages LLM reasoning with code execution and integrated biomedical databases.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fbiomni\u002FSKILL.md",[352,355],{"categoryNo":353,"categoryName":354,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[348,357,267,358,359,360,361,362,363,364,365,366,367,243,368,369,370,334,371,335,372,373,339,374,319,375],"design","ai agent","agent framework","interpretation","tasks","code","reasoning","protocol","framework","Optimization","execution","autonomous","databases","across","RNA","clinical","diagnosis","seq","prediction",{"skillNo":377,"name":378,"nameZh":13,"description":379,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":380,"categories":381,"keywords":384,"publishedAt":232},"01M6AFACQF9SMSEPJ6P1225A17","benchling-integration","Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fbenchling-integration\u002FSKILL.md",[382,383],{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":23,"categoryName":24,"taxonomyType":6,"taxonomyTypeDesc":7},[385,386,387,285,388,222,389,268,270,226,390,391,392,393,394,272,395,396,397,230],"integration","benchling integration","automation","registry","inventory","entries","DNA","proteins","platform","apps","data management","warehouse","lab",{"skillNo":399,"name":400,"nameZh":13,"description":401,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":402,"categories":403,"keywords":408,"publishedAt":232},"01M6AFA9YQ51JG7AP9R7DM521W","astropy","Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fastropy\u002FSKILL.md",[404,407],{"categoryNo":405,"categoryName":406,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[400,409,284,361,410,330,222,243,290,411,412,413,414,415,416,417,253,418,230,319],"data analysis","library","files","coordinate","world","time","astrophysics","unit","processing","tables",{"skillNo":420,"name":421,"nameZh":13,"description":422,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":423,"categories":424,"keywords":425,"publishedAt":232},"01M6AFA7NAE825VQW20NDJSPYX","arboreto","Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Farboreto\u002FSKILL.md",[],[421,426,427,222,428,429,371,430,431,432,249,433,434,435,436,374,230,437,254,319,438],"distributed","analyzing","networks","algorithms","gene expression","factor","infer","grnboost2","transcriptomics","bulk","Scalable","gene","computation",{"skillNo":440,"name":441,"nameZh":13,"description":442,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":443,"categories":444,"keywords":446,"publishedAt":232},"01M6AFA4GZ24E48QPESYX3W76T","anndata","This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy\u002Fscverse tools.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fanndata\u002FSKILL.md",[445],{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[441,284,361,311,385,222,447,243,244,290,411,448,449,450,371,451,253,374,230,254,319],"Tools","datasets","objects","genomics","h5ad",{"skillNo":453,"name":454,"nameZh":13,"description":455,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":456,"categories":457,"keywords":459,"publishedAt":232},"01M6AFA1Z3M2387C05FNR9X7E2","alphafold-database","Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB\u002FmmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Falphafold-database\u002FSKILL.md",[458],{"categoryNo":212,"categoryName":213,"taxonomyType":53,"taxonomyTypeDesc":54},[218,460,461,462,223,270,463,464,411,465,466,292,228,336,339,230,467],"alphafold database","alphafold","metrics","download","analyze","structural biology","structural","Protein",{"skillNo":469,"name":470,"nameZh":13,"description":471,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":472,"categories":473,"keywords":475,"publishedAt":232},"01M6AF9YGRX68JBQDEDY3XZHNJ","aeon","This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Faeon\u002FSKILL.md",[474],{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[470,476,477,361,478,221,479,222,480,481,482,483,243,484,485,486,414,429,487,488,230,489,319],"machine learning","ml","learn","time series","Similarity Search","clustering","detection","segmentation","regression","specialized","patterns","scikit-learn","time series analysis","anomaly",{"skillNo":491,"name":492,"nameZh":13,"description":493,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":494,"categories":495,"keywords":498,"publishedAt":232},"01M6AF9VPZPPMZ8TSPF2Z85JJE","adaptyv","Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fadaptyv\u002FSKILL.md",[496,497],{"categoryNo":212,"categoryName":213,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[492,499,357,285,500,501,502,503,366,447,268,504,392,505,393,249,506,507,230,342,319,508,467],"testing","experiments","status","validation","cloud","experiment","computational","solublempnn","activity","sequences",{"skillNo":510,"name":511,"nameZh":13,"description":512,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":513,"categories":514,"keywords":519,"publishedAt":232},"01M6AF9RMACYMHSCDZQ4RA4QM0","railway-templates","Search and deploy services from Railway's template marketplace. Use when user wants to add a service from a template, find templates for a specific use case, or deploy tools like Ghost, Strapi, n8n, Minio, Uptime Kuma, etc. For databases (Postgres, Redis, MySQL, MongoDB), prefer the railway-database skill.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Frailway\u002Ftemplates\u002FSKILL.md",[515,518],{"categoryNo":516,"categoryName":517,"taxonomyType":53,"taxonomyTypeDesc":54},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[520,521,522,523,387,524,525,526,218,527,221,528,529,530,531,286,447,532,533,534,369,535,536,537,538,319],"templates","railway templates","Railway","cli","deploy","infrastructure","deployment","mysql","uptime","redis","cms","marketplace","mongodb","Bash","template","postgres","add","strapi","kuma",{"skillNo":540,"name":541,"nameZh":13,"description":542,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":543,"categories":544,"keywords":546,"publishedAt":232},"01M6AF9PT8TVRGSH6F02BBYSMX","railway-status","Check current Railway project status for this directory. Use when user asks \"railway status\", \"is it running\", \"what's deployed\", \"deployment status\", or about uptime. NOT for variables or configuration queries - use railway-environment skill for those.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Frailway\u002Fstatus\u002FSKILL.md",[545],{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[501,547,522,548,523,525,526,528,533,549,550,551,552,290,291,553,554,555,230,556,319,557],"railway status","directory","check","command","environment","project status","project","Variables","which","use railway","running",{"skillNo":559,"name":560,"nameZh":13,"description":561,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":562,"categories":563,"keywords":566,"publishedAt":232},"01M6AF9MAEXPJ32AXBRP55WEMX","railway-service","Check service status, rename services, change service icons, link services, or create services with Docker images. For creating services with local code, prefer railway-new skill. For GitHub repo sources, use railway-new skill to create empty service then railway-environment skill to configure source.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Frailway\u002Fservice\u002FSKILL.md",[564,565],{"categoryNo":516,"categoryName":517,"taxonomyType":53,"taxonomyTypeDesc":54},{"categoryNo":215,"categoryName":216,"taxonomyType":53,"taxonomyTypeDesc":54},[567,568,522,523,152,569,570,501,525,571,572,362,286,533,573,574,575,576,577,578,579,230,580,581],"railway service","service","docker","change","create","icons","configure","repo","images","new skill","rename","local","sources","source","new",{"skillNo":583,"name":584,"nameZh":13,"description":585,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":586,"categories":587,"keywords":588,"publishedAt":232},"01M6AF9JJ3P0E0WFZMQDJ0RFMH","railway-docs","Fetch up-to-date Railway documentation to answer questions accurately. Use when user asks about Railway features, how Railway works, or shares a docs.railway.com URL.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Frailway\u002Frailway-docs\u002FSKILL.md",[],[589,590,522,523,591,592,593,594,595,596,290,597,598,599,600,601,602,603,319],"docs","railway docs","documentation","help","how","learning","user","fetch","up","reference","about","questions","URL","answer","features",158,18]