Enforces unidirectional data flow with clear ownership. Use when reviewing data flows, debugging race conditions, or designing state management. Prevents ghost updates and synchronization bugs.
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data-warehouse
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Data warehouse design mastery with star schema, dimensional modeling, fact/dimension tables, slowly changing dimensions, and enterprise best practices. Complete schema examples included.
explore-data
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Explores data in a Bauplan lakehouse safely using the Bauplan Python SDK. Use to inspect namespaces, tables, schemas, samples, and profiling queries; and to export larger result sets to files....
data-visualization
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Creates effective data visualizations, charts, dashboards, and reports across analytics, infrastructure monitoring, and ML domains. Covers library selection, UX design, and accessibility. Trigger...
data-reproducibility
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Infrastructure and practices for reproducible computational research. Covers environment management, data versioning, code documentation, and sharing protocols that enable others to reproduce your...
Pandas Data Analysis
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Master data manipulation, analysis, and visualization with Pandas, NumPy, and Matplotlib
data-jupyter-python
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Guidelines for data analysis and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
Expert guidance for data analysis, visualization, and Jupyter Notebook development with pandas, matplotlib, seaborn, and numpy.
Expert in data forensics, anomaly detection, audit trail analysis, fraud detection, and breach investigation
Everyday data transformations using functional patterns - arrays, objects, grouping, aggregation, and null-safe access
data-model-creation
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Optional advanced tool for complex data modeling. For simple table creation, use relational-database-tool directly with SQL statements.
Extract and validate data from requests including JSON, forms, query parameters, and path parameters. Use for handling user input and API payloads.
data-analysis-sql
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SQL for data analysis with exploratory analysis, advanced aggregations, statistical functions, outlier detection, and business insights. 50+ real-world analytics queries.
native-data-fetching
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Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, axios, React Query, SWR, error handling, caching strategies, offline support.
Organize and categorize files into logical structures. Creates folder hierarchies, renames files systematically, and consolidates related data.
Use when designing databases for data-heavy applications, making schema decisions for performance, choosing between normalization and denormalization, selecting storage/indexing strategies,...
core-data-expert
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Expert Core Data guidance (iOS/macOS): stack setup, fetch requests & NSFetchedResultsController, saving/merge conflicts, threading & Swift Concurrency, batch operations & persistent history,...
Use when implementing or modifying data analysis backend features including endpoints, aggregations, dimensions, or formatters. Ensures Clean Architecture principles, three-layer separation...
csv-data-summarizer
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Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.
Use when starting technical work requiring structured approach - writing tests before code (TDD), planning data exploration (EDA), designing statistical analysis, clarifying modeling objectives...