bouclem

Best practices and guidelines for Apache Kafka event streaming and distributed messaging

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Apache Airflow, dbt, Prefect, Dagster, and modern data orchestration for production data pipelines

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Snowflake, BigQuery, Redshift, dimensional modeling, and modern data warehouse architecture

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Expert data scientist for advanced analytics, machine learning, and statistical modeling. Handles complex data analysis, predictive modeling, and business intelligence.

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Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

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Data pipeline architecture, ETL/ELT patterns, data modeling, and production data platform design

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You are a data pipeline architecture expert specializing in scalable, reliable, and cost-effective data pipelines for batch and streaming data processing.

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Data analysis best practices with pandas, numpy, matplotlib, seaborn, and Jupyter notebooks.

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Complete toolkit for senior architect with modern tools and best practices.

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Build read models and projections from event streams. Use when implementing CQRS read sides, building materialized views, or optimizing query performance in event-sourced systems.

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Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.

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Scaffolds eval.yaml test files for agent skills in the dotnet/skills repository. Use when creating skill tests, writing evaluation scenarios, defining assertions and rubrics, or setting up test fixture files. Handles eval.yaml generation, fixture organization, and overfitting avoidance. Do not use for running or debugging existing tests nor for skills authoring.

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SymPy is a Python library for symbolic mathematics that enables exact computation using mathematical symbols rather than numerical approximations.

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Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots.

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Automate Supabase database queries, table management, project administration, storage, edge functions, and SQL execution via Rube MCP (Composio). Always search tools first for current schemas.

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Statistics, probability, linear algebra, and mathematical foundations for data science

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Best practices for Matplotlib data visualization, plotting, and creating publication-quality figures in Python

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MongoDB, Redis, Cassandra, DynamoDB, and distributed database patterns for scalable applications

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Creates VS Code custom agent files (.agent.md) for specialized AI personas with tools, instructions, and handoffs. Use when scaffolding new custom agents, configuring agent workflows, or setting up agent-to-agent handoffs.

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PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.

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Guide for quality focused software architecture. This skill should be used when users want to write code, design architecture, analyze code, in any case that relates to software development.

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Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.

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Astropy is the core Python package for astronomy, providing essential functionality for astronomical research and data analysis.

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