[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skills:pro6":3,"skills:creators9":50,"skills:sce6":148,"skills:stats":193,"skills:all:stars:156:":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 Analyst","数据分析、报表与商业智能人员",4988,[],{"categoryNo":30,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":31,"categoryNameEn":32,"description":33,"level":11,"skillCount":34,"parentNo":13,"parentName":13,"children":35},"01JBSEEDCAT000000000000036","内容创作者","Content Creator","作者、编辑与自媒体创作者",3940,[],{"categoryNo":37,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":38,"categoryNameEn":39,"description":40,"level":11,"skillCount":41,"parentNo":13,"parentName":13,"children":42},"01JBSEEDCAT000000000000035","市场营销","Marketer","市场推广、增长与品牌运营人员",3446,[],{"categoryNo":44,"taxonomyType":6,"taxonomyTypeDesc":7,"categoryName":45,"categoryNameEn":46,"description":47,"level":11,"skillCount":48,"parentNo":13,"parentName":13,"children":49},"01JBSEEDCAT000000000000037","律师与法务","Legal","合同、合规与法律事务人员",3316,[],{"records":51,"total":146,"current":11,"size":147},[52,66,75,85,95,105,115,124,134],{"accountNo":53,"login":54,"displayName":55,"avatarUrl":56,"accountType":57,"accountTypeDesc":58,"profileDescription":59,"skillCount":60,"repoCount":61,"professionCount":62,"scenarioCount":63,"totalStars":64,"updatedAt":65},"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":67,"login":68,"displayName":68,"avatarUrl":69,"accountType":57,"accountTypeDesc":58,"profileDescription":70,"skillCount":71,"repoCount":72,"professionCount":63,"scenarioCount":63,"totalStars":73,"updatedAt":74},"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":76,"login":77,"displayName":78,"avatarUrl":79,"accountType":57,"accountTypeDesc":58,"profileDescription":13,"skillCount":80,"repoCount":81,"professionCount":63,"scenarioCount":82,"totalStars":83,"updatedAt":84},"01M6AC29YGCR4S2NTJFV0G8B81","openai","OpenAI","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F14957082?v=4",171,23,6,342695,"2026-11-13 04:03:41",{"accountNo":86,"login":87,"displayName":88,"avatarUrl":89,"accountType":57,"accountTypeDesc":58,"profileDescription":13,"skillCount":90,"repoCount":91,"professionCount":92,"scenarioCount":63,"totalStars":93,"updatedAt":94},"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":96,"login":97,"displayName":98,"avatarUrl":99,"accountType":57,"accountTypeDesc":58,"profileDescription":100,"skillCount":101,"repoCount":102,"professionCount":62,"scenarioCount":63,"totalStars":103,"updatedAt":104},"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":106,"login":107,"displayName":108,"avatarUrl":109,"accountType":57,"accountTypeDesc":58,"profileDescription":110,"skillCount":111,"repoCount":112,"professionCount":62,"scenarioCount":63,"totalStars":113,"updatedAt":114},"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":116,"login":117,"displayName":118,"avatarUrl":119,"accountType":57,"accountTypeDesc":58,"profileDescription":13,"skillCount":120,"repoCount":121,"professionCount":62,"scenarioCount":63,"totalStars":122,"updatedAt":123},"01M697XGDPXJAVQ8391V2BCYTE","anthropics","Anthropic","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F76263028?v=4",674,17,231826,"2026-11-13 04:18:26",{"accountNo":125,"login":126,"displayName":127,"avatarUrl":128,"accountType":57,"accountTypeDesc":58,"profileDescription":13,"skillCount":129,"repoCount":130,"professionCount":131,"scenarioCount":63,"totalStars":132,"updatedAt":133},"01M6AC83EPDGBFN19MWYRREJD0","Significant-Gravitas","AutoGPT","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F130738209?v=4",86,2,10,188014,"2026-11-13 02:38:59",{"accountNo":135,"login":136,"displayName":137,"avatarUrl":138,"accountType":139,"accountTypeDesc":140,"profileDescription":141,"skillCount":142,"repoCount":143,"professionCount":82,"scenarioCount":63,"totalStars":144,"updatedAt":145},"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",1926,9,[149,158,165,172,179,186],{"categoryNo":150,"taxonomyType":151,"taxonomyTypeDesc":152,"categoryName":153,"categoryNameEn":154,"description":155,"level":11,"skillCount":156,"parentNo":13,"parentName":13,"children":157},"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",39458,[],{"categoryNo":159,"taxonomyType":151,"taxonomyTypeDesc":152,"categoryName":160,"categoryNameEn":161,"description":162,"level":11,"skillCount":163,"parentNo":13,"parentName":13,"children":164},"01JBSEEDCAT000000000000006","软件开发","Software Development","编码、测试、部署等软件研发任务",26531,[],{"categoryNo":166,"taxonomyType":151,"taxonomyTypeDesc":152,"categoryName":167,"categoryNameEn":168,"description":169,"level":11,"skillCount":170,"parentNo":13,"parentName":13,"children":171},"01JBSEEDCAT000000000000014","设计创意","Design & Creative","视觉设计、品牌与多媒体创作",13569,[],{"categoryNo":173,"taxonomyType":151,"taxonomyTypeDesc":152,"categoryName":174,"categoryNameEn":175,"description":176,"level":11,"skillCount":177,"parentNo":13,"parentName":13,"children":178},"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":180,"taxonomyType":151,"taxonomyTypeDesc":152,"categoryName":181,"categoryNameEn":182,"description":183,"level":11,"skillCount":184,"parentNo":13,"parentName":13,"children":185},"01JBSEEDCAT000000000000017","内容创作","Content Creation","写作、文案与营销内容生产",6029,[],{"categoryNo":187,"taxonomyType":151,"taxonomyTypeDesc":152,"categoryName":188,"categoryNameEn":189,"description":190,"level":11,"skillCount":191,"parentNo":13,"parentName":13,"children":192},"01JBSEEDCAT000000000000020","研究与学习","Research & Learning","资料检索、知识整理与学习辅导",5531,[],{"skillCount":194,"professionCount":62,"scenarioCount":63,"creatorCount":146},196852,{"records":196,"total":194,"current":608,"size":609},[197,238,271,298,326,345,366,398,423,442,456,480,499,519,538,557,573,592],{"skillNo":198,"name":199,"nameZh":13,"description":200,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":209,"categories":210,"keywords":218,"publishedAt":237},"01M6AFF7WA662AHQMWFG48G9WK","hypothesis-generation","Generate testable hypotheses. Formulate from observations, design experiments, explore competing explanations, develop predictions, propose mechanisms, for scientific inquiry across domains.","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\u002Fhypothesis-generation\u002FSKILL.md",[211,214,217],{"categoryNo":212,"categoryName":213,"taxonomyType":151,"taxonomyTypeDesc":152},"01JBSEEDCAT000000000000015","视觉设计",{"categoryNo":215,"categoryName":216,"taxonomyType":151,"taxonomyTypeDesc":152},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":16,"categoryName":17,"taxonomyType":6,"taxonomyTypeDesc":7},[219,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,236],"hypothesis","hypothesis generation","generation","design","experiments","generate","Bash","explore","develop","read","write","edit","across","domains","predictions","scientific","observations","for","2026-11-10 10:12:30",{"skillNo":239,"name":240,"nameZh":13,"description":241,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":242,"categories":243,"keywords":251,"publishedAt":237},"01M6AFF49SFV1VXXX3N5EMFKS7","hypogenic","Automated hypothesis generation and testing using large language models. Use this skill when generating scientific hypotheses from datasets, combining literature insights with empirical data, testing hypotheses against observational data, or conducting systematic hypothesis exploration for research discovery in domains like deception detection, AI content detection, mental health analysis, or other empirical research tasks.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fhypogenic\u002FSKILL.md",[244,247,250],{"categoryNo":245,"categoryName":246,"taxonomyType":151,"taxonomyTypeDesc":152},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":248,"categoryName":249,"taxonomyType":151,"taxonomyTypeDesc":152},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":215,"categoryName":216,"taxonomyType":151,"taxonomyTypeDesc":152},[240,252,253,254,255,256,257,219,258,259,260,261,262,263,264,265,266,267,268,269,232,234,236,270],"testing","large language models","research","tasks","content","data","deception","detection","analysis","discovery","health","use","models","datasets","exploration","mental health","systematic","literature","language models",{"skillNo":272,"name":273,"nameZh":13,"description":274,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":275,"categories":276,"keywords":280,"publishedAt":237},"01M6AFF1JH5764GS5FY1RAAKPT","hmdb-database","Access Human Metabolome Database (220K+ metabolites). Search by name\u002FID\u002Fstructure, retrieve chemical properties, biomarker data, NMR\u002FMS spectra, pathways, for metabolomics and identification.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fhmdb-database\u002FSKILL.md",[277],{"categoryNo":278,"categoryName":279,"taxonomyType":151,"taxonomyTypeDesc":152},"01JBSEEDCAT000000000000010","后端与接口",[281,282,283,284,257,285,286,287,288,289,290,291,292,293,294,295,296,236,297],"database","hmdb database","hmdb","search","access","ms","properties","structure","human","chemical","id","name","metabolomics","biomarker","identification","pathways","by name",{"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":308,"publishedAt":237},"01M6AFEYD8V314EFABN2X6K9NV","histolab","Digital pathology image processing toolkit for whole slide images (WSI). Use this skill when working with histopathology slides, processing H&E or IHC stained tissue images, extracting tiles from gigapixel pathology images, detecting tissue regions, segmenting tissue masks, or preparing datasets for computational pathology deep learning pipelines. Applies to WSI formats (SVS, TIFF, NDPI), tile-based analysis, and histological image preprocessing workflows.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fhistolab\u002FSKILL.md",[304,307],{"categoryNo":305,"categoryName":306,"taxonomyType":151,"taxonomyTypeDesc":152},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":215,"categoryName":216,"taxonomyType":151,"taxonomyTypeDesc":152},[300,309,310,311,312,260,313,314,315,263,316,317,318,319,320,321,322,323,236,324,325],"image","workflows","deep learning","toolkit","learning","slides","image processing","images","deep","computational","preprocessing","processing","detecting","extracting","formats","pathology","when",{"skillNo":327,"name":328,"nameZh":13,"description":329,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":330,"categories":331,"keywords":334,"publishedAt":237},"01M6AFEVGG4NKXDVCME27VSJYC","gwas-database","Query NHGRI-EBI GWAS Catalog for SNP-trait associations. Search variants by rs ID, disease\u002Ftrait, gene, retrieve p-values and summary statistics, for genetic epidemiology and polygenic risk scores.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fgwas-database\u002FSKILL.md",[332,333],{"categoryNo":278,"categoryName":279,"taxonomyType":151,"taxonomyTypeDesc":152},{"categoryNo":215,"categoryName":216,"taxonomyType":151,"taxonomyTypeDesc":152},[281,335,284,336,337,338,339,340,291,341,342,236,343,344],"gwas database","risk","catalog","summary","query","statistics","epidemiology","values","gene","variants",{"skillNo":346,"name":347,"nameZh":13,"description":348,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":349,"categories":350,"keywords":351,"publishedAt":237},"01M6AFERS36D2N817E7FV4G1AA","gtars","High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fgtars\u002FSKILL.md",[],[347,352,353,354,355,356,312,259,357,260,313,358,263,359,318,360,361,362,363,364,365,236,325],"python","performance","rust","machine learning","ml","applications","coverage","files","bed","high-performance","machine","Tokenization","tracks","fragment",{"skillNo":367,"name":368,"nameZh":13,"description":369,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":370,"categories":371,"keywords":373,"publishedAt":237},"01M6AFEK2MJ3C166PKCCTMRHHN","get-available-resources","This skill should be used at the start of any computationally intensive scientific task to detect and report available system resources (CPU cores, GPUs, memory, disk space). It creates a JSON file with resource information and strategic recommendations that inform computational approach decisions such as whether to use parallel processing (joblib, multiprocessing), out-of-core computing (Dask, Zarr), GPU acceleration (PyTorch, JAX), or memory-efficient strategies. Use this skill before running analyses, training models, processing large datasets, or any task where resource constraints matter.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fget-available-resources\u002FSKILL.md",[372],{"categoryNo":215,"categoryName":216,"taxonomyType":151,"taxonomyTypeDesc":152},[374,375,376,377,378,379,380,381,382,383,384,385,386,387,388,389,390,318,391,392,234,320,393,394,395,396,397],"get available resources","get","resources","memory","pytorch","training","core","report","gpu","file","start","Memory-Efficient","constraints","dask","disk","parallel","strategies","recommendations","as","CPU","GPU Acceleration","information","at","running",{"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":237},"01M6AFEFZZ10W8DYEKM63Z68SZ","geopandas","Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading\u002Fwriting\u002Fanalyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib\u002Ffolium\u002Fcartopy. Use for tasks like buffer analysis, spatial joins between datasets, dissolving boundaries, clipping data, calculating areas\u002Fdistances, reprojecting coordinate systems, creating maps, or converting between spatial file formats.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fgeopandas\u002FSKILL.md",[404,407],{"categoryNo":405,"categoryName":406,"taxonomyType":151,"taxonomyTypeDesc":152},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":30,"categoryName":31,"taxonomyType":6,"taxonomyTypeDesc":7},[400,409,352,255,410,411,412,383,413,414,257,260,415,359,416,417,418,419,323,420,236,421,422,325],"writing","vector","geospatial","library","integration","analyzing","databases","maps","coordinate","mapping","reading","buffer","spatial joins","overlay",{"skillNo":424,"name":425,"nameZh":13,"description":426,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":427,"categories":428,"keywords":430,"publishedAt":237},"01M6AFEDA8P0XB4M4F0B6MDK11","geo-database","Access NCBI GEO for gene expression\u002Fgenomics data. Search\u002Fdownload microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT\u002FMatrix files, for transcriptomics and expression analysis.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fgeo-database\u002FSKILL.md",[429],{"categoryNo":278,"categoryName":279,"taxonomyType":151,"taxonomyTypeDesc":152},[281,431,432,284,257,260,285,433,359,265,434,435,436,437,438,439,440,236,343,441],"geo database","geo","download","genomics","RNA","gene expression","expression","transcriptomics","seq","matrix","NCBI",{"skillNo":443,"name":444,"nameZh":13,"description":445,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":446,"categories":447,"keywords":449,"publishedAt":237},"01M6AFEAB6RHM2V8PHSZNVC6K3","geniml","This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fgeniml\u002FSKILL.md",[448],{"categoryNo":215,"categoryName":216,"taxonomyType":151,"taxonomyTypeDesc":152},[444,355,450,356,379,255,451,383,257,260,313,452,263,359,453,454,360,362,439,236,455,325],"accessibility","embeddings","consensus","feature","collections","single",{"skillNo":457,"name":458,"nameZh":13,"description":459,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":460,"categories":461,"keywords":466,"publishedAt":237},"01M6AFE7SNVWPCJDEAC17BGZ2T","generate-image","Generate or edit images using AI models (FLUX, Gemini). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that isn't a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fgenerate-image\u002FSKILL.md",[462,465],{"categoryNo":463,"categoryName":464,"taxonomyType":151,"taxonomyTypeDesc":152},"01JBSEEDCAT000000000000016","图像与多媒体",{"categoryNo":215,"categoryName":216,"taxonomyType":151,"taxonomyTypeDesc":152},[309,224,467,468,469,470,471,230,263,316,472,473,474,475,476,234,477,478,479,236],"generate image","gemini","diagram","Image Generation","technical","diagrams","Art","general","visual","flux","ai models","schematic","concept",{"skillNo":481,"name":482,"nameZh":13,"description":483,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":484,"categories":485,"keywords":488,"publishedAt":237},"01M6AFE5K5YGF3ASF6EVFSQCME","gene-database","Query NCBI Gene via E-utilities\u002FDatasets API. Search by symbol\u002FID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fgene-database\u002FSKILL.md",[486,487],{"categoryNo":278,"categoryName":279,"taxonomyType":151,"taxonomyTypeDesc":152},{"categoryNo":5,"categoryName":8,"taxonomyType":6,"taxonomyTypeDesc":7},[281,489,343,490,284,491,260,492,265,339,493,291,494,495,496,497,236,498,441],"gene database","go","batch","api","info","annotation","via","functional","Utilities","functional analysis",{"skillNo":500,"name":501,"nameZh":13,"description":502,"descriptionZh":13,"repositoryFullName":201,"ownerLogin":202,"ownerAvatarUrl":203,"ownerAccountNo":204,"ownerDisplayName":205,"repositoryNo":206,"starsCount":207,"licenseSpdxId":208,"licenseFileUrl":13,"sourceHtmlUrl":503,"categories":504,"keywords":505,"publishedAt":237},"01M6AFE38AAP06XD9WYNADAPZ8","fluidsim","Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D\u002F3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. 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