[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"creator:01M6ESH7EXPXTH9CVQ4K16SRG8":3,"creator-list:01M6ESH7EXPXTH9CVQ4K16SRG8:stars:1:":21},{"accountNo":4,"login":5,"displayName":6,"avatarUrl":7,"accountType":8,"accountTypeDesc":9,"profileDescription":10,"skillCount":11,"repoCount":12,"professionCount":13,"scenarioCount":14,"totalStars":15,"updatedAt":16,"htmlUrl":17,"blogUrl":18,"company":18,"location":19,"followersCount":20,"publicReposCount":13},"01M6ESH7EXPXTH9CVQ4K16SRG8","henriquescastilho","Henrique Scheer","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F153296945?v=4","USER","个人作者","Software · Applied AI · Quantitative Modeling · Building with Claude.",943,1,10,7,0,"2026-06-10 12:24:46","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho",null,"Rio de Janeiro, BR",9,{"records":22,"total":11,"current":12,"size":434},[23,69,78,87,109,137,169,198,221,246,266,282,304,327,351,372,396,416],{"skillNo":24,"name":25,"nameZh":18,"description":26,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":30,"categories":31,"keywords":48,"publishedAt":68},"01M6F0B6XPQ65AX2X0DWK8KT3E","markitdown","Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.","henriquescastilho\u002Fmy-claude","01M6ESH7JHEK2PTNNH4HEH787Z","MIT","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-writer\u002Fskills\u002Fmarkitdown\u002FSKILL.md",[32,37,40,43],{"categoryNo":33,"categoryName":34,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",{"categoryNo":38,"categoryName":39,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000003","演示文稿",{"categoryNo":41,"categoryName":42,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000004","电子表格",{"categoryNo":44,"categoryName":45,"taxonomyType":46,"taxonomyTypeDesc":47},"01JBSEEDCAT000000000000034","行政与办公人员","PROFESSION","适用职业",[25,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67],"docx","PDF","pptx","xlsx","documents","csv","ocr","Audio","Bash","markdown","convert","read","write","edit","html","images","files","youtube","with","2026-11-10 10:12:30",{"skillNo":70,"name":25,"nameZh":18,"description":26,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":71,"categories":72,"keywords":77,"publishedAt":68},"01M6F06SBHR9F0SDWE282Y8075","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-writer\u002Fscientific_writer\u002F.claude\u002Fskills\u002Fmarkitdown\u002FSKILL.md",[73,74,75,76],{"categoryNo":33,"categoryName":34,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":38,"categoryName":39,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":41,"categoryName":42,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":44,"categoryName":45,"taxonomyType":46,"taxonomyTypeDesc":47},[25,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67],{"skillNo":79,"name":25,"nameZh":18,"description":26,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":80,"categories":81,"keywords":86,"publishedAt":68},"01M6F02D4R14EJAPBWVDF9J9VQ","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-writer\u002F.claude\u002Fskills\u002Fmarkitdown\u002FSKILL.md",[82,83,84,85],{"categoryNo":33,"categoryName":34,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":38,"categoryName":39,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":41,"categoryName":42,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":44,"categoryName":45,"taxonomyType":46,"taxonomyTypeDesc":47},[25,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67],{"skillNo":88,"name":89,"nameZh":18,"description":90,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":91,"categories":92,"keywords":93,"publishedAt":68},"01M6F000KS6YB4MKS774G4R8ND","zarr-python","Chunked N-D arrays for cloud storage. Compressed arrays, parallel I\u002FO, S3\u002FGCS integration, NumPy\u002FDask\u002FXarray compatible, for large-scale scientific computing pipelines.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fzarr-python\u002FSKILL.md",[],[94,95,96,97,98,99,100,101,102,103,104,105,106,107,108],"python","zarr python","storage","integration","s3","gcs","cloud","dask","parallel","pipelines","arrays","numpy","scientific computing","scale","scientific",{"skillNo":110,"name":111,"nameZh":18,"description":112,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":113,"categories":114,"keywords":118,"publishedAt":68},"01M6EZZJWFXM1GR78KTW6J0DN8","what-if-oracle","Run structured What-If scenario analysis with multi-branch possibility exploration. Use this skill when the user asks speculative questions like \"what if...\", \"what would happen if...\", \"what are the possibilities\", \"explore scenarios\", \"scenario analysis\", \"possibility space\", \"what could go wrong\", \"best case \u002F worst case\", \"risk analysis\", \"contingency planning\", \"strategic options\", or any question about uncertain futures. Also trigger when the user faces a fork-in-the-road decision, wants to stress-test an idea, or needs to think through consequences before committing.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fwhat-if-oracle\u002FSKILL.md",[115],{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000023","Skill与智能体开发",[119,120,121,122,123,124,125,126,127,128,129,60,61,130,131,132,133,134,135,136],"oracle","what if oracle","go","run","ux","futures","analysis","explore","decision","branch","question","idea","exploration","options","stress-test","strategies","scenario","stress",{"skillNo":138,"name":139,"nameZh":18,"description":140,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":141,"categories":142,"keywords":153,"publishedAt":68},"01M6EZZCXAEB49RXGQCJX5E8GB","venue-templates","Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). This skill should be used when preparing manuscripts for journal submission, conference papers, research posters, or grant proposals and need venue-specific formatting requirements and templates.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fvenue-templates\u002FSKILL.md",[143,146,149,150],{"categoryNo":144,"categoryName":145,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":147,"categoryName":148,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":151,"categoryName":152,"taxonomyType":46,"taxonomyTypeDesc":47},"01JBSEEDCAT000000000000036","内容创作者",[154,155,156,157,158,159,160,161,57,162,60,61,62,163,164,165,166,167,108,168],"templates","venue templates","research","guidelines","NeurIPS","ICML","LaTeX","science","access","proposals","Academic","requirements","formatting","journal","chi",{"skillNo":170,"name":171,"nameZh":18,"description":172,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":173,"categories":174,"keywords":179,"publishedAt":68},"01M6EZZ77X6VQAVZGQP2988YJ0","vaex","Use this skill for processing and analyzing large tabular datasets (billions of rows) that exceed available RAM. Vaex excels at out-of-core DataFrame operations, lazy evaluation, fast aggregations, efficient visualization of big data, and machine learning on large datasets. Apply when users need to work with large CSV\u002FHDF5\u002FArrow\u002FParquet files, perform fast statistics on massive datasets, create visualizations of big data, or build ML pipelines that do not fit in memory.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fvaex\u002FSKILL.md",[175,178],{"categoryNo":176,"categoryName":177,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000013","分析与可视化",{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},[171,180,181,182,183,184,185,186,187,188,189,190,191,192,65,193,194,195,196,197],"memory","machine learning","core","create","visualization","dataframe","Evaluation","analyzing","data","in memory","visualizations","learning","work","do","statistics","fit","processing","ML Pipelines",{"skillNo":199,"name":200,"nameZh":18,"description":201,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":202,"categories":203,"keywords":210,"publishedAt":68},"01M6EZYYTQ9X7ECKCCMY8HG3QT","usfiscaldata","Query the U.S. Treasury Fiscal Data API for federal financial data including national debt, government spending, revenue, interest rates, exchange rates, and savings bonds. Access 54 datasets and 182 data tables with no API key required. Use when working with U.S. federal fiscal data, national debt tracking (Debt to the Penny), Daily Treasury Statements, Monthly Treasury Statements, Treasury securities auctions, interest rates on Treasury securities, foreign exchange rates, savings bonds, or any U.S. government financial statistics.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fusfiscaldata\u002FSKILL.md",[204,207],{"categoryNo":205,"categoryName":206,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":208,"categoryName":209,"taxonomyType":46,"taxonomyTypeDesc":47},"01JBSEEDCAT000000000000030","开发工程师",[200,211,188,212,162,213,214,215,216,217,218,194,219,220,67],"savings","api","tracking","use","daily","datasets","query","exchange","monthly","revenue",{"skillNo":222,"name":223,"nameZh":18,"description":224,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":225,"categories":226,"keywords":231,"publishedAt":68},"01M6EZYHG2QA778W9CQ23VKM8W","treatment-plans","Generate concise (3-4 page), focused medical treatment plans in LaTeX\u002FPDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Ftreatment-plans\u002FSKILL.md",[227,228],{"categoryNo":33,"categoryName":34,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":229,"categoryName":230,"taxonomyType":46,"taxonomyTypeDesc":47},"01JBSEEDCAT000000000000037","律师与法务",[232,233,50,234,235,57,236,237,60,61,62,238,239,240,241,166,242,243,244,245],"treatment plans","plans","generate","Citations","text","page","evidence","goal","frameworks","mental health","medical","clinical","professional","brevity",{"skillNo":247,"name":248,"nameZh":18,"description":249,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":250,"categories":251,"keywords":252,"publishedAt":68},"01M6EZY64SQP4PMCGC9X9ZN3TF","torch-geometric","Graph Neural Networks (PyG). Node\u002Fgraph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Ftorch-geometric\u002FSKILL.md",[],[253,254,255,256,257,258,191,259,260,261,262,263,264,265],"torch geometric","deep learning","neural networks","graph","networks","classification","node","Neural","deep","graphs","molecular","gat","link",{"skillNo":267,"name":268,"nameZh":18,"description":269,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":270,"categories":271,"keywords":272,"publishedAt":68},"01M6EZXWCYH1CR0DG8Q095BNAK","tiledbvcf","Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF\u002FBCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Ftiledbvcf\u002FSKILL.md",[],[268,96,273,188,102,274,275,276,277,278,279,280,281],"capabilities","export","ingestion","queries","sample","genomics","vcf","retrieval","Scalable",{"skillNo":283,"name":284,"nameZh":18,"description":285,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":286,"categories":287,"keywords":292,"publishedAt":68},"01M6EZX9PB6KWNAMM0AXZAW5YF","statistical-analysis","Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fstatistical-analysis\u002FSKILL.md",[288,291],{"categoryNo":289,"categoryName":290,"taxonomyType":35,"taxonomyTypeDesc":36},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},[125,293,156,294,295,296,188,297,298,214,299,300,301,302,164,303,67],"statistical analysis","test","help","reporting","statsmodels","results","power","models","guidance","selection","tests",{"skillNo":305,"name":306,"nameZh":18,"description":307,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":308,"categories":309,"keywords":311,"publishedAt":68},"01M6EZX4QS3EMSM07MTG2HTYS9","stable-baselines3","Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fstable-baselines3\u002FSKILL.md",[310],{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},[312,313,314,315,316,317,318,212,191,102,214,319,320,321,322,323,324,325,67,326],"stable baselines3","performance","training","learn","vectorized","PPO","pufferlib","ready","rl","scikit-learn","reinforcement","high-performance","prototyping","multi","quick",{"skillNo":328,"name":329,"nameZh":18,"description":330,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":331,"categories":332,"keywords":334,"publishedAt":68},"01M6EZWZX8G2B7RJGD4B8DKY1J","simpy","Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fsimpy\u002FSKILL.md",[333],{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},[329,94,335,336,337,338,339,340,214,341,342,343,344,345,346,347,348,349,350,67],"framework","network","simulation","system","operations","process","time","shared","service","systems","as","events","resources","manufacturing","processes","event",{"skillNo":352,"name":353,"nameZh":18,"description":354,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":355,"categories":356,"keywords":358,"publishedAt":68},"01M6EZWVN8RBS0D8CX7MDT28BP","shap","Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fshap\u002FSKILL.md",[357],{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},[353,359,181,254,360,361,362,187,191,363,214,261,364,365,366,367,368,369,370,371],"tensorflow","pytorch","debugging","linear","model","bias","feature","black","random forest","predictions","machine","Interpretability","random",{"skillNo":373,"name":374,"nameZh":18,"description":375,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":376,"licenseFileUrl":18,"sourceHtmlUrl":377,"categories":378,"keywords":380,"publishedAt":68},"01M6EZWFXPEBP9S5XW1MN8BVHC","scvelo","RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced\u002Fspliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy\u002FscVI-tools for trajectory inference.","BSD-3-Clause","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fscvelo\u002FSKILL.md",[379],{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},[374,381,188,382,125,383,384,385,341,386,387,388,389,390,391,392,393,394,395,67],"state","Tools","scanpy","velocity","compute","transitions","RNA","cell","infer","single-cell","trajectory","scvi","dynamics","driver","rna-seq",{"skillNo":397,"name":398,"nameZh":18,"description":399,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":400,"categories":401,"keywords":405,"publishedAt":68},"01M6EZVX5BTCDN9JM0XB89WM6M","scientific-writing","Core skill for the deep research and writing tool. Write scientific manuscripts in full paragraphs (never bullet points). Use two-stage process with (1) section outlines with key points using research-lookup then (2) convert to flowing prose. IMRAD structure, citations (APA\u002FAMA\u002FVancouver), figures\u002Ftables, reporting guidelines (CONSORT\u002FSTROBE\u002FPRISMA), for research papers and journal submissions.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fscientific-writing\u002FSKILL.md",[402,403,404],{"categoryNo":144,"categoryName":145,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":151,"categoryName":152,"taxonomyType":46,"taxonomyTypeDesc":47},[406,407,108,182,296,408,235,409,57,410,60,61,62,411,412,261,413,414,167,415],"writing","scientific writing","deep research","Outlines","tool","never","structure","full","prisma","figures",{"skillNo":417,"name":418,"nameZh":18,"description":419,"descriptionZh":18,"repositoryFullName":27,"ownerLogin":5,"ownerAvatarUrl":7,"ownerAccountNo":4,"ownerDisplayName":6,"repositoryNo":28,"starsCount":15,"licenseSpdxId":29,"licenseFileUrl":18,"sourceHtmlUrl":420,"categories":421,"keywords":424,"publishedAt":68},"01M6EZVQEZPEC2AFWPFN653FYV","scientific-visualization","Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib\u002Fseaborn\u002Fplotly with publication styles. For quick exploration use seaborn or plotly directly.","https:\u002F\u002Fgithub.com\u002Fhenriquescastilho\u002Fmy-claude\u002Fblob\u002Fmain\u002F.codex\u002Fvendor_imports\u002Fclaude\u002Fmarketplaces\u002Fclaude-scientific-skills\u002Fscientific-skills\u002Fscientific-visualization\u002FSKILL.md",[422,423],{"categoryNo":176,"categoryName":177,"taxonomyType":35,"taxonomyTypeDesc":36},{"categoryNo":116,"categoryName":117,"taxonomyType":35,"taxonomyTypeDesc":36},[184,425,108,426,427,428,429,161,430,214,319,131,431,166,167,432,433,67,415,326],"scientific visualization","safe","Meta","plotly","seaborn","annotations","meta-skill","panel","error",18]