[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6CY76YBAG706GDWNJ8HX7BS":3,"skill-same:01M6CY76YBAG706GDWNJ8HX7BS":54},{"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":26,"linkOnly":27,"markdownContent":28,"markdownBody":29,"frontMatter":30,"refName":33,"commitSha":34,"skillDirectory":35,"forksCount":14,"repositoryHtmlUrl":36,"repositoryHomepageUrl":6,"ownerHtmlUrl":37,"ownerBlogUrl":38,"ownerDescription":6,"updatedAt":39,"install":40,"resources":53},"01M6CY76YBAG706GDWNJ8HX7BS","leakage-checklist",null,"How to recognise data leakage: features unavailable at prediction time or proxies for the target.","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\u002Fleakage-checklist\u002FSKILL.md",[],[19,20,21,22,23,24,25],"checklist","leakage checklist","data","how","knowledge","time","proxies","2026-11-10 10:12:30",false,"---\nname: leakage-checklist\ndescription: \"How to recognise data leakage: features unavailable at prediction time or proxies for the target.\"\nmetadata:\n  beyondml:\n    kind: knowledge\n---\nLeakage is a feature that would not exist when the prediction is made, or that is a proxy for the target.\n\n- Recorded after the outcome: a churn model's Cancellation_Date, a fraud model's chargeback flag.\n- Direct functions of the target: Tax_Amount for Price, total = sum of parts that include the target.\n- Treatment implies diagnosis: a disease model's Prescription_A.\n- IDs and timestamps that encode the split or the label order.\n- Too good to be true: a single column that scores 0.98+ on its own almost always leaks.\n\nAction: drop high-risk columns; for medium risk, keep them only with a written justification.\n","Leakage is a feature that would not exist when the prediction is made, or that is a proxy for the target.\n\n- Recorded after the outcome: a churn model's Cancellation_Date, a fraud model's chargeback flag.\n- Direct functions of the target: Tax_Amount for Price, total = sum of parts that include the target.\n- Treatment implies diagnosis: a disease model's Prescription_A.\n- IDs and timestamps that encode the split or the label order.\n- Too good to be true: a single column that scores 0.98+ on its own almost always leaks.\n\nAction: drop high-risk columns; for medium risk, keep them only with a written justification.\n",{"name":5,"metadata":31,"description":7},{"beyondml":32},{"kind":23},"main","724a833f3e23c83a25b2ded06208fe53a1a1f460","beyondml\u002Fskills\u002Fleakage-checklist","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":41,"prompt":51,"zipAvailable":52},[42,45,48],{"tool":43,"command":44},"npx","npx skills add Riteesh-2k6\u002Fbeyondml --skill leakage-checklist",{"tool":46,"command":47},"bunx","bunx skills add Riteesh-2k6\u002Fbeyondml --skill leakage-checklist",{"tool":49,"command":50},"pnpm","pnpm dlx skills add Riteesh-2k6\u002Fbeyondml --skill leakage-checklist","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Fbeyondml\u002Fskills\u002Fleakage-checklist\u002FSKILL.md",true,[],[55,69,77,85,100,121],{"skillNo":56,"name":57,"nameZh":6,"description":58,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":59,"categories":60,"keywords":61,"publishedAt":26},"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",[],[62,63,64,65,21,66,67,68],"tabular demo","demo","read","finish","file","run","python",{"skillNo":70,"name":71,"nameZh":6,"description":72,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":73,"categories":74,"keywords":75,"publishedAt":26},"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",[],[63,76,23],"leakage demo",{"skillNo":78,"name":79,"nameZh":6,"description":80,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":81,"categories":82,"keywords":83,"publishedAt":26},"01M6CY7YDZB93PX14NDCJDBPRX","bad-name","Name does not match its folder.","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Ftests\u002Fdata\u002Fskills\u002FBadName\u002FSKILL.md",[],[84],"bad name",{"skillNo":86,"name":87,"nameZh":6,"description":88,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":89,"categories":90,"keywords":96,"publishedAt":26},"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",[91],{"categoryNo":92,"categoryName":93,"taxonomyType":94,"taxonomyTypeDesc":95},"01JBSEEDCAT000000000000008","测试与质量","SCENARIO","使用场景",[97,98,99,21,22,23],"test","train","train test split",{"skillNo":101,"name":102,"nameZh":6,"description":103,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":104,"categories":105,"keywords":106,"publishedAt":26},"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",[],[107,108,109,110,111,65,112,113,114,64,115,68,67,66,116,117,21,118,119,120],"tabular features","list","user","profile","use","files","scan","eda","write","logs","csv","src","check","ask",{"skillNo":122,"name":123,"nameZh":6,"description":124,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":125,"categories":126,"keywords":127,"publishedAt":26},"01M6CY7Q2GNHM2NM7ZVRMGRX7P","tabular-export","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.","https:\u002F\u002Fgithub.com\u002FRiteesh-2k6\u002Fbeyondml\u002Fblob\u002Fmain\u002Fbeyondml\u002Fskills\u002Ftabular-export\u002FSKILL.md",[],[128,129,65,67,130,131,66,132,133,118,134,135,136,64,115,108,112,137,98,68],"tabular export","export","code","search","pipeline","classification","model","regression","evolve","models"]