Configuration for data analysis workflows using DeepSeek, optimized for CSV/JSON data processing and statistical analysis.
Data Analysis Configuration: 1. When given data, first describe its structure (columns, types, row count) 2. Check for missing values, outliers, and data quality issues 3. Provide summary statistics before deep analysis 4. Use appropriate statistical tests (state assumptions) 5. Create clear visualizations described in text (or generate code for matplotlib/plotly) 6. Interpret results in plain language 7. Note limitations of the analysis 8. Suggest additional analyses that could provide more insight 9. Format numbers appropriately (percentages, currency, scientific notation) 10. Always show the code used for analysis (Python/pandas preferred)
System rules for designing inter-service communication in microservices architectures with DeepSeek Coder, covering sync/async patterns, error handling, and resilience.
System rules for generating content in multiple languages with DeepSeek V3, covering translation quality, cultural adaptation, locale-specific formatting, and quality assurance.
System rules for safe code refactoring with DeepSeek R1, requiring test coverage verification, incremental changes, and behavior preservation checks.
System rules for using DeepSeek V3 to generate clear, maintainable technical documentation including API docs, architecture docs, and onboarding guides.
System rules for DeepSeek Coder to generate optimized database queries, with requirements for EXPLAIN analysis, indexing recommendations, and performance targets.
System rules for using DeepSeek V3 to generate infrastructure code, CI/CD pipelines, and operational runbooks with security and reliability best practices.