[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"creator:01M6DT9WNJJ470ADHPSMFAA02Y":3,"creator-list:01M6DT9WNJJ470ADHPSMFAA02Y:stars:1:":19},{"accountNo":4,"login":5,"displayName":5,"avatarUrl":6,"accountType":7,"accountTypeDesc":8,"profileDescription":9,"skillCount":10,"repoCount":11,"professionCount":12,"scenarioCount":13,"totalStars":14,"updatedAt":15,"htmlUrl":16,"blogUrl":9,"company":9,"location":9,"followersCount":17,"publicReposCount":18},"01M6DT9WNJJ470ADHPSMFAA02Y","TianGzlab","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F150978281?v=4","ORGANIZATION","组织",null,91,1,3,4,161,"2026-10-08 01:36:11","https:\u002F\u002Fgithub.com\u002FTianGzlab",12,6,{"records":20,"total":10,"current":11,"size":347},[21,44,56,73,99,122,144,160,183,201,218,234,251,267,286,305,320,331],{"skillNo":22,"name":23,"nameZh":9,"description":24,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":28,"categories":29,"keywords":35,"publishedAt":43},"01M6DTP4X225Q92RMY8XXHPCTT","demo-skill","A fixture skill for the skill environment tests. Use it for nothing else.","TianGzlab\u002FOmicsClaw","01M6DT9WSN09C5K65GB6RK18R9","Apache-2.0","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Ftests\u002Fskillenv\u002Ffixtures\u002Fskills\u002Fdemo\u002Fdemo-skill\u002FSKILL.md",[30],{"categoryNo":31,"categoryName":32,"taxonomyType":33,"taxonomyTypeDesc":34},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[36,37,38,39,40,41,42],"demo","demo skill","environment","use","fixture skill","fixture","tests","2026-11-10 10:12:30",{"skillNo":45,"name":46,"nameZh":9,"description":47,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":48,"categories":49,"keywords":50,"publishedAt":43},"01M6DTP28JTWQK3HHXDNQV8BBV","fake-domains","Test fixture for the golden deployment in tests\u002Fentry. Load never; it has no script.","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Ftests\u002Fentry\u002Ffake_skills\u002Fspatial\u002Ffake-domains\u002FSKILL.md",[],[51,52,53,54,55,41,42],"domains","fake domains","test","deployment","never",{"skillNo":57,"name":58,"nameZh":9,"description":59,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":60,"categories":61,"keywords":63,"publishedAt":43},"01M6DTNZ4AMWKTME1T18K5C643","replace-me-skill","Load when copying this directory to bootstrap a new OmicsClaw skill. Skip when an existing skill already covers the request.","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Ftemplates\u002Fskill\u002FSKILL.md",[62],{"categoryNo":31,"categoryName":32,"taxonomyType":33,"taxonomyTypeDesc":34},[64,65,66,67,68,69,70,71,72],"me","replace me skill","directory","scaffold","bootstrap","template","new skill","existing skill","skill template",{"skillNo":74,"name":75,"nameZh":9,"description":76,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":77,"categories":78,"keywords":79,"publishedAt":43},"01M6DTNV63MTD0Q6YRC52F0B1Y","spatial-velocity","Load when estimating RNA velocity on a spatial AnnData with `layers[\"spliced\"]` + `layers[\"unspliced\"]` via scVelo (stochastic \u002F deterministic \u002F dynamical) or veloVI (deep generative). Skip when input lacks the spliced\u002Funspliced layers (must be quantified upstream by velocyto \u002F kb-python \u002F STARsolo); non-spatial scRNA velocity (use sc-velocity).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-velocity\u002FSKILL.md",[],[80,81,82,83,84,39,85,86,87,88,89,90,91,92,93,94,95,96,97,98],"Spatial","velocity","spatial velocity","python","kb","deterministic","upstream","time","deep","RNA","scvelo","input","starsolo","kb-python","via","velocyto","rna-velocity","velovi","dynamics",{"skillNo":100,"name":101,"nameZh":9,"description":102,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":103,"categories":104,"keywords":105,"publishedAt":43},"01M6DTNPMR227NAT8QFY620YDW","spatial-trajectory","Load when inferring pseudotime \u002F lineage trajectories on a preprocessed spatial AnnData via DPT (default — diffusion pseudotime), CellRank (terminal-state + fate-probability), or Palantir (waypoint branch probabilities). Skip when the data has spliced\u002Funspliced layers and you want velocity-driven dynamics (use spatial-velocity); non-spatial scRNA pseudotime (use sc-pseudotime).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-trajectory\u002FSKILL.md",[],[80,106,107,108,109,110,111,112,113,39,114,81,115,116,117,118,119,120,94,121],"trajectory","spatial trajectory","terminal","state","lineage","data","anndata","branch","default","cell","probability","diffusion","pseudotime","dpt","palantir","cellrank",{"skillNo":123,"name":124,"nameZh":9,"description":125,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":126,"categories":127,"keywords":128,"publishedAt":43},"01M6DTNJEYFT33P84DGHDNXW95","spatial-statistics","Load when running spatial autocorrelation \u002F hotspot \u002F co-occurrence \u002F neighbourhood-enrichment \u002F Ripley K stats on a clustered spatial AnnData via squidpy. Skip when ranking spatially variable genes (use spatial-genes); tissue domain detection (use spatial-domains).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-statistics\u002FSKILL.md",[],[80,129,130,131,132,133,112,39,134,135,136,137,94,51,138,139,140,141,142,143],"statistics","spatial statistics","stats","enrichment","detection","domain","local","autocorrelation","ranking","neighbourhood","moran","geary","ripley","co-occurrence","nhood-enrichment",{"skillNo":145,"name":146,"nameZh":9,"description":147,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":148,"categories":149,"keywords":150,"publishedAt":43},"01M6DTNF4HP2WP971HD2QZ8TG8","spatial-register","Load when aligning multiple spatial slices into a common coordinate frame with PASTE or STalign. Skip single-slice data; for expression-space batch correction use spatial-integrate.","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-register\u002FSKILL.md",[],[80,151,152,153,111,154,39,155,156,157,158,159],"register","spatial register","batch","common","integrate","alignment","registration","coordinate","expression",{"skillNo":161,"name":162,"nameZh":9,"description":163,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":164,"categories":165,"keywords":166,"publishedAt":43},"01M6DTNBT4Y062PT5BWYEM8AE5","spatial-raw-processing","Load when converting spatial transcriptomics raw FASTQ pairs through ST-Pipeline into a `raw_counts.h5ad` ready for spatial-preprocess. Skip when input is already a count-matrix AnnData (use spatial-preprocess); non-spatial bulk \u002F scRNA FASTQ (use bulkrna-read-qc).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-raw-processing\u002FSKILL.md",[],[80,167,168,169,170,171,39,172,173,86,91,174,175,176,177,178,179,180,181,182],"spatial raw processing","file","pipeline","ids","read","ready","coordinates","qc","bulkrna","spatial transcriptomics","count-matrix","FASTQ","visium","raw-processing","st-pipeline","slideseq",{"skillNo":184,"name":185,"nameZh":9,"description":186,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":187,"categories":188,"keywords":189,"publishedAt":43},"01M6DTN7H322DKGNXSX8QTQ3CG","spatial-preprocess","Load when running the foundational spatial transcriptomics QC + filtering + normalisation + HVG + PCA + neighbour-graph + Leiden pipeline on a Visium \u002F Xenium \u002F generic spatial AnnData. Skip when raw FASTQs need converting first (use spatial-raw-processing); tissue-domain detection on already-preprocessed data (use spatial-domains).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-preprocess\u002FSKILL.md",[],[80,190,169,133,191,192,193,39,134,194,195,196,197,174,176,198,199,51,179,200],"spatial preprocess","first","normalization","filtering","preprocessing","normalize","umap","PCA","leiden","hvg","xenium",{"skillNo":202,"name":203,"nameZh":9,"description":204,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":205,"categories":206,"keywords":207,"publishedAt":43},"01M6DTN38E4W9TY0ZXBNXWCR83","spatial-microenvironment-subset","Load when extracting a niche \u002F microenvironment subset around a center cell-type by spatial radius from a labelled spatial AnnData, producing a smaller AnnData of centers + their within-radius neighbours. Skip when running global tissue-domain detection (use spatial-domains); cross-condition comparison (use spatial-condition).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-microenvironment-subset\u002FSKILL.md",[],[80,208,133,209,112,210,39,134,115,211,212,213,214,51,215,216,217,138,179,200],"spatial microenvironment subset","radius","extract","type","cell-type","tumor","condition","microenvironment","niche","subsetting",{"skillNo":219,"name":220,"nameZh":9,"description":221,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":222,"categories":223,"keywords":224,"publishedAt":43},"01M6DTMZY0M18YJM789GGY8EEJ","spatial-integrate","Load when removing batch effects from multi-batch spatial AnnData with PCA using Harmony, BBKNN, or Scanorama. Skip physical coordinate alignment (use spatial-register) and single-batch data (use spatial-domains).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-integrate\u002FSKILL.md",[],[155,80,225,153,226,111,112,39,156,158,227,228,151,197,229,230,231,232,233,51],"spatial integrate","integration","sample","physical","batch-correction","harmony","bbknn","scanorama","multi-sample",{"skillNo":235,"name":236,"nameZh":9,"description":237,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":238,"categories":239,"keywords":240,"publishedAt":43},"01M6DTMTDP01YT15VZRA6NZAWX","spatial-genes","Load when ranking spatially variable genes with Moran's I, SpatialDE, SPARK-X, or FlashS. Skip when detecting tissue domains (use spatial-domains) or differential expression between groups (use spatial-de).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-genes\u002FSKILL.md",[],[80,241,242,39,243,136,244,159,137,245,51,246,247,248,249,250],"spatial genes","spark","pattern","SVG","de","spatially-variable-genes","morans-i","spatialde","sparkx","flashs",{"skillNo":252,"name":253,"nameZh":9,"description":254,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":255,"categories":256,"keywords":257,"publishedAt":43},"01M6DTMPHQEX6AYZ34YPX3C6B5","spatial-enrichment","Load when running pathway or gene-set enrichment per cluster on spatial AnnData with over-representation, preranked GSEA, or ssGSEA group-mean scores. Skip when ranking spatially variable genes (use spatial-genes) or comparing conditions (use spatial-condition).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-enrichment\u002FSKILL.md",[],[132,80,258,259,260,112,39,137,261,262,263,214,264,265,266],"spatial enrichment","go","SET","GSEA","Reactome","pathway","ssgsea","enrichr","gene-set",{"skillNo":268,"name":269,"nameZh":9,"description":270,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":271,"categories":272,"keywords":273,"publishedAt":43},"01M6DTMJ6WBQ006AF100S7QTQ1","spatial-domains","Load when detecting tissue domains \u002F niches on a preprocessed spatial AnnData via Leiden \u002F Louvain (spatial-weighted) or graph-neural backends (SpaGCN \u002F STAGATE \u002F GraphST \u002F BANKSY \u002F CellCharter). Skip when ranking spatially variable genes (use spatial-genes); spot-level cell-type annotation (use spatial-annotate).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-domains\u002FSKILL.md",[],[80,274,39,275,276,134,277,211,137,278,198,279,94,51,280,281,282,283,284,285],"spatial domains","Neural","annotate","spot","identification","louvain","niches","spagcn","stagate","graphst","banksy","cellcharter",{"skillNo":287,"name":288,"nameZh":9,"description":289,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":290,"categories":291,"keywords":292,"publishedAt":43},"01M6DTMDMZ9ZZ6X0WJYJ5C1N1P","spatial-deconv","Load when deconvolving spot-level cell-type proportions on a Visium-style spatial AnnData using a labelled scRNA reference (FlashDeconv \u002F Cell2location \u002F RCTD \u002F DestVI \u002F Tangram \u002F others). Skip when each spot is a single cell already (Xenium \u002F MERFISH) (use spatial-annotate); tissue-domain detection (use spatial-domains).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-deconv\u002FSKILL.md",[],[80,293,133,39,294,276,134,277,115,211,295,296,297,298,299,300,301,302,303,304],"spatial deconv","reference","style","single cell","deconvolution","cell2location","rctd","destvi","stereoscope","spotlight","card","flashdeconv",{"skillNo":306,"name":307,"nameZh":9,"description":308,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":309,"categories":310,"keywords":311,"publishedAt":43},"01M6DTMA0FWHNVPAD5KYP9DFX0","spatial-de","Load when ranking spatial cluster markers or comparing two spatial groups. Skip when the data is single-cell (use sc-de), bulk (use bulkrna-de), or for spatially variable expression (use spatial-genes).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-de\u002FSKILL.md",[],[80,245,312,53,111,313,39,115,314,159,137,315,316,175,317,318,319],"spatial de","pydeseq2","t-test","single-cell","differential-expression","wilcoxon","markers","pseudobulk",{"skillNo":321,"name":322,"nameZh":9,"description":323,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":324,"categories":325,"keywords":326,"publishedAt":43},"01M6DTM6CQ8R3GCBFA04728GJC","spatial-condition","Load when comparing conditions on spatial AnnData using biological-sample pseudobulk PyDESeq2 or Wilcoxon, with sample, condition and cluster labels. Skip one-condition per-cluster DE (use spatial-de) and experiments without independent replicates.","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-condition\u002FSKILL.md",[],[80,327,328,112,313,39,227,329,159,316,330,245,317,214,319],"spatial condition","experiments","control","DESeq2",{"skillNo":332,"name":333,"nameZh":9,"description":334,"descriptionZh":9,"repositoryFullName":25,"ownerLogin":5,"ownerAvatarUrl":6,"ownerAccountNo":4,"ownerDisplayName":9,"repositoryNo":26,"starsCount":14,"licenseSpdxId":27,"licenseFileUrl":9,"sourceHtmlUrl":335,"categories":336,"keywords":337,"publishedAt":43},"01M6DTM2XB8499QEQHSYNF6BYG","spatial-communication","Load when computing ligand-receptor communication on labelled spatial AnnData with LIANA, CellPhoneDB, FastCCC or CellChat. Skip unlabelled data (use spatial-annotate) and non-spatial scRNA analysis (use sc-cell-communication).","https:\u002F\u002Fgithub.com\u002FTianGzlab\u002FOmicsClaw\u002Fblob\u002Fmain\u002Fskills\u002Fspatial\u002Fspatial-communication\u002FSKILL.md",[],[338,80,339,111,112,340,39,276,115,341,342,343,344,345,346],"communication","spatial communication","analysis","scrna","cell-communication","ligand-receptor","liana","cellphonedb","cellchat",18]