[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CY7Q2GNHM2NM7ZVRMGRX7P":3,"skill-same:01M6CY7Q2GNHM2NM7ZVRMGRX7P":70},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":49,"commitSha":50,"skillDirectory":51,"forksCount":14,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":54,"ownerDescription":6,"updatedAt":55,"install":56,"resources":69},"01M6CY7Q2GNHM2NM7ZVRMGRX7P","tabular-export",null,"Writes the shipped code (src\u002Fpipeline.py, src\u002Ftrain.py, src\u002Fpredict.py) from the winning run and trains it. Usually right after evolve-search or tabular-ensemble. Check: run src\u002Ftrain.py, expects models\u002Fmodel.joblib, metric accuracy (classification) or r2 (regression) with a minimum.","Riteesh-2k6\u002Fbeyondml","Riteesh-2k6","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F140528424?v=4","01M6CY6V18JEE5K6V3V28ZWQNK","Riteesh Thiruveedhula","01M6CY6V5BAR5VMFSG62KXRNA4",0,"MIT","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Fbeyondml\u002Fskills\u002Ftabular-export\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"tabular export","export","evolve","train","models","files","finish","list","write","read","python","regression","model","src","classification","pipeline","file","search","code","run","2026-11-10 10:12:30",false,"---\nname: tabular-export\ndescription: \"Writes the shipped code (src\u002Fpipeline.py, src\u002Ftrain.py, src\u002Fpredict.py) from the winning run and trains it. Usually right after evolve-search or tabular-ensemble. Check: run src\u002Ftrain.py, expects models\u002Fmodel.joblib, metric accuracy (classification) or r2 (regression) with a minimum.\"\nallowed-tools: read_file list_files write_file run_python export_pipeline finish_step\nmetadata:\n  beyondml:\n    kind: step\n    modality: tabular\n---\nYou turn the winning run into code that works without BeyondML.\n\n1. Call export_pipeline(run_id=\u003Cthe run_id from the upstream summary, or \"\" for the latest>).\n2. src\u002Ftrain.py already applies clean(df) and make_features(df) when src\u002Fclean.py and src\u002Ffeatures.py exist; do not duplicate them.\n3. Run run_python(\"src\u002Ftrain.py\"). If it fails, read stderr_tail and fix the code (usually a column mismatch between features.py and the exported FEATURES list), then run it again.\n4. Call finish_step with the reported score, outputs=[\"src\u002Fpipeline.py\", \"src\u002Ftrain.py\", \"src\u002Fpredict.py\", \"models\u002Fmodel.joblib\"].\n","You turn the winning run into code that works without BeyondML.\n\n1. Call export_pipeline(run_id=\u003Cthe run_id from the upstream summary, or \"\" for the latest>).\n2. src\u002Ftrain.py already applies clean(df) and make_features(df) when src\u002Fclean.py and src\u002Ffeatures.py exist; do not duplicate them.\n3. Run run_python(\"src\u002Ftrain.py\"). If it fails, read stderr_tail and fix the code (usually a column mismatch between features.py and the exported FEATURES list), then run it again.\n4. Call finish_step with the reported score, outputs=[\"src\u002Fpipeline.py\", \"src\u002Ftrain.py\", \"src\u002Fpredict.py\", \"models\u002Fmodel.joblib\"].\n",{"name":5,"metadata":44,"description":7,"allowed-tools":48},{"beyondml":45},{"kind":46,"modality":47},"step","tabular","read_file list_files write_file run_python export_pipeline finish_step","main","724a833f3e23c83a25b2ded06208fe53a1a1f460","beyondml\u002Fskills\u002Ftabular-export","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6","riteeshvnsp.onrender.com","2026-10-25 14:58:25",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add Riteesh-2k6\u002Fbeyondml --skill tabular-export",{"tool":62,"command":63},"bunx","bunx skills add Riteesh-2k6\u002Fbeyondml --skill tabular-export",{"tool":65,"command":66},"pnpm","pnpm dlx skills add Riteesh-2k6\u002Fbeyondml --skill tabular-export","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Fbeyondml\u002Fskills\u002Ftabular-export\u002FSKILL.md",true,[],[71,81,90,98,113,130],{"skillNo":72,"name":73,"nameZh":6,"description":74,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":75,"categories":76,"keywords":77,"publishedAt":39},"01M6CY8269784EN3M5TCSD07EB","tabular-demo","Demo step skill for tabular data.","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Ftests\u002Fdata\u002Fskills\u002Ftabular-demo\u002FSKILL.md",[],[78,79,38,29,35,80,28,25],"tabular demo","demo","data",{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":39},"01M6CY80AQNXNZT62N6GQZXA52","leakage-demo","Demo knowledge skill about target leakage.","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Ftests\u002Fdata\u002Fskills\u002Fleakage-demo\u002FSKILL.md",[],[79,88,89],"leakage demo","knowledge",{"skillNo":91,"name":92,"nameZh":6,"description":93,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":94,"categories":95,"keywords":96,"publishedAt":39},"01M6CY7YDZB93PX14NDCJDBPRX","bad-name","Name does not match its folder.","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Ftests\u002Fdata\u002Fskills\u002FBadName\u002FSKILL.md",[],[97],"bad name",{"skillNo":99,"name":100,"nameZh":6,"description":101,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":102,"categories":103,"keywords":109,"publishedAt":39},"01M6CY7VZ7MJXVVQ5GCKTJWEXV","train-test-split","How to split data so the score is honest.","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Fbeyondml\u002Fskills\u002Ftrain-test-split\u002FSKILL.md",[104],{"categoryNo":105,"categoryName":106,"taxonomyType":107,"taxonomyTypeDesc":108},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",[110,22,111,89,112,80],"test","train test split","how",{"skillNo":114,"name":115,"nameZh":6,"description":116,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":117,"categories":118,"keywords":119,"publishedAt":39},"01M6CY7SHBNZXKWXVNYXJFJRX3","tabular-features","Writes src\u002Ffeatures.py with derived features (ratios, logs, interactions) and no target use. Usually right after tabular-eda. Check: run src\u002Ffeatures.py, expects data\u002Fprocessed\u002Ffeatures.csv.","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Fbeyondml\u002Fskills\u002Ftabular-features\u002FSKILL.md",[],[120,25,121,122,24,123,29,38,35,124,80,32,125,126,28,27,26,127,128,129],"tabular features","eda","scan","csv","logs","check","ask","user","profile","use",{"skillNo":131,"name":132,"nameZh":6,"description":133,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":134,"categories":135,"keywords":136,"publishedAt":39},"01M6CY7NH83619YG0SVN22YVWT","tabular-ensemble","Combines the search's top models into a stacking ensemble. Only when the top genomes are within about 1% of each other. Check: metric cv_score with a minimum.","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Fbeyondml\u002Fskills\u002Ftabular-ensemble\u002FSKILL.md",[],[137,35,125,28,138,25,23,36],"tabular ensemble","only"]