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Everything your AI needs, in one place.
Ready-made agents, skills, personas, prompts, templates and tools. Each one is checked before it goes live, works with any model, and installs in a click. Rate what you use so the best rises to the top.
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A service that does a whole job for you - research, coding, support - and reports back.
Step-by-step instructions an AI follows for one kind of task. Install once, reuse everywhere.
A voice and set of rules layered onto any model: tone, audience, do's and don'ts.
A ready-to-use prompt with fill-in-the-blank variables and notes on when it works best.
A complete routing setup - models, rules and settings - in one file you can apply in a minute.
A single function an AI can call: a calculator, a search, a database lookup.
A language model endpoint with its price, speed and quality declared so the router can compare it.
data-science-expert
Expert-level data science, analytics, visualization, and statistical modeling. Use when the user mentions analytics, visualization, statistics, pandas, or NumPy, or when the task involves Data Analysi
ml-expert
Expert-level machine learning, deep learning, model training, and MLOps. Use when the user mentions machine learning, deep learning, neural networks, MLOps, or data science, or when the task involves
julia-expert
Expert knowledge in Julia scientific computing, multiple dispatch, performance optimization, and numerical analysis. Use when the user mentions scientific computing, multiple dispatch, performance, nu
data-scientist
Data science across machine learning, statistical modeling, and experimentation. Use when selecting ML algorithms, engineering features, designing A/B tests, evaluating model performance, or building
senior-data-scientist
Expert data science for statistical modeling, experimentation, ML deployment, and data-driven decision making — A/B test design and analysis, feature engineering, model training/evaluation, production
orchestration-engineer
Data pipeline orchestration covering Apache Airflow DAG design patterns, Dagster software-defined assets, Prefect flow composition, retry and backfill strategies, dependency management, dynamic task g
orchestration-engineer
Data pipeline orchestration covering Apache Airflow DAG design patterns, Dagster software-defined assets, Prefect flow composition, retry and backfill strategies, dependency management, dynamic task g
loops
AI驱动的自动化循环集合。覆盖软件开发、数据科学、内容创作、产品运营、学习管理等领域。当用户需要自动化工作流、修复问题、生成内容、分析数据或执行质量检查时使用。
moai-domain-data-science
Production-grade data science specialist with TensorFlow 2.20.0, PyTorch 2.9.0, Scikit-learn 1.7.2 expertise. Master data processing, ML pipeline development, model deployment, and statistical analysi
Find
Search or browse by kind. Every card shows who made it, how many people installed it and what they think.
Install
One click. You get a manifest the router understands, plus copy-paste snippets for the CLI, Python and YAML.
Rate and publish
Leave a star rating after you have used it. Made something useful? Publish it - free listings go live immediately.
Prefer the terminal? osr stack apply registry://starter installs the starter template.