Design and troubleshoot robust data pipelines with comprehensive quality validation, error handling, and monitoring capabilities for bioinformatics and data processing workflows

Process data files through transformation pipelines with validation, cleaning, and export. Use for CSV/Excel/JSON data processing, encoding handling, batch operations, and data transformation workflows.

Orchestrate marketing data collection, transformation, and reporting workflows. Use when relevant to the task.

Load and preprocess imaging mass cytometry (IMC) and MIBI data. Covers MCD/TIFF handling, hot pixel removal, and image normalization. Use when starting IMC analysis from raw MCD files or preparing images for segmentation.

Profile datasets to understand schema, quality, and characteristics. Use when analyzing data files (CSV, JSON, Parquet), discovering dataset properties, assessing data quality, or when user mentions data profiling, schema detection, data analysis, or quality metrics. Provides basic and intermediate profiling including distributions, uniqueness, and pattern detection.

Assess data quality with checks for missing values, duplicates, type issues, and inconsistencies. Use for data validation, ETL pipelines, or dataset documentation.

Comprehensive guide to data quality validation, testing frameworks, anomaly detection, and data observability for production data pipelines

Generate comprehensive dbt test suites following FF Analytics data quality standards and dbt 1.10+ syntax. This skill should be used when creating tests for new dbt models, adding tests to existing models, standardizing test coverage, or implementing data quality gates. Covers grain uniqueness, FK relationships, enum validation, and freshness tests.

Systematic framework for catching data quality issues, query errors, metric calculation problems, and inconsistencies before they affect analysis results.

Data discovery and analysis specialist focused on extracting actionable insights from complex datasets, identifying patterns and anomalies, and transforming raw data into strategic intelligence. Excels at multi-source data integration, advanced analytics, and data-driven decision support.

Expert data researcher specializing in discovering, collecting, and analyzing diverse data sources. Masters data mining, statistical analysis, and pattern recognition with focus on extracting meaningful insights from complex datasets to support evidence-based decisions.

Comprehensive data safety auditor for Vue 3 + Pinia + IndexedDB + PouchDB applications. Detects data loss risks, sync issues, race conditions, and browser-specific vulnerabilities with actionable remediation guidance.

Expert-level data science, analytics, visualization, and statistical modeling

Expert in statistical analysis, predictive modeling, machine learning, and data storytelling to drive business insights.

Create database seed scripts with realistic test data for development and testing. Use when setting up development environment or creating demo data.

Production-grade SQL optimization for OLTP systems: EXPLAIN/plan analysis, balanced indexing, schema and query design, migrations, backup/recovery, HA, security, and safe performance tuning across PostgreSQL, MySQL, SQL Server, Oracle, SQLite.

Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

Use when designing databases for data-heavy applications, making schema decisions for performance, choosing between normalization and denormalization, selecting storage/indexing strategies, planning for scale, or evaluating OLTP vs OLAP trade-offs. Also use when encountering N+1 queries, ORM issues, or concurrency problems.

Create Next.js data table pages with SSR initial load, SWR caching, and server-response-based UI updates. Use when asked to create a new data table page, entity management page, CRUD table, or admin list view. Generates page.tsx (SSR), table components, columns, context, actions, and API routes following a proven architecture with centralized reusable data-table component.

Data-to-UI pipeline patterns. Use when transforming JSON data into React components, creating TypeScript types from schemas, building derived types, or creating data utilities.

Transform, clean, reshape, and preprocess data using pandas and numpy. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

Effect provides immutable, type-safe data structures:

Generate interactive validation reports with quality scoring, missing data analysis, and type checking. Combines Pandas validation, Plotly visualization, and YAML configuration for comprehensive data quality reporting.

data-visualizer

Interactive data exploration and visualization skill. Use when users ask to visualize data, analyze datasets, create charts, or explore data files (CSV, Excel, Parquet, JSON). This skill guides through data exploration, proposes visualization strategies based on data characteristics, creates interactive Plotly charts in marimo notebooks, and generates analytical conclusions.

Data warehouse (大数据/数仓) ops skill for designing and operating analytical data platforms. Use for tasks like defining source-of-truth, building ETL/ELT pipelines, dimensional modeling (star schema), data quality checks, partitioning strategies, cost/performance tuning, governance, lineage, and SLA monitoring.

AgentSkill for https://idx.md. Use the index to locate AI agent library topics and fetch HEAD/BODY markdown.

Expert for developing Streamlit data apps for Keboola deployment. Activates when building, modifying, or debugging Keboola data apps, Streamlit dashboards, adding filters, creating pages, or fixing data app issues. Validates data structures using Keboola MCP before writing code, tests implementations with Playwright browser automation, and follows SQL-first architecture patterns.

Automate backups, replication, and performance tuning.

database-administrator

Analyze and optimize database schemas, identify performance issues, and suggest improvements. Use when working with database structure, indexes, or query performance.

Database architecture and design specialist. Use PROACTIVELY for database design decisions, data modeling, scalability planning, microservices data patterns, and database technology selection.

MANDATORY when designing schemas, writing migrations, creating indexes, or making architectural database decisions - enforces PostgreSQL 18 best practices including AIO, UUIDv7, temporal constraints, and modern indexing strategies

Auditoria e análise de bancos de dados para identificar anomalias, inconsistências, registros órfãos, duplicatas, índices faltantes, e problemas de integridade referencial. Usar para diagnosticar problemas de dados, preparar migrações, gerar relatórios de qualidade de dados, identificar foreign keys quebradas, e otimizar estrutura de tabelas.

Backup database before tests, migrations, or other database operations

Implement backup and restore strategies for disaster recovery. Use when creating backup plans, testing restore procedures, or setting up automated backups.

database-change-management

Database MCP server integration for PostgreSQL, MySQL, MongoDB

Expert in database schema design with focus on normalization, indexing strategies, FTS optimization, and performance-oriented architecture for desktop applications

Database schema design patterns and optimization strategies for relational and NoSQL databases. Use when designing database schemas, optimizing query performance, or implementing data persistence layers at scale.

Je vais concevoir un schéma de base de données complet avec ERD, migrations et optimisations.

Advanced database design and administration for PostgreSQL, MongoDB, and Redis. Use when designing schemas, optimizing queries, managing database performance, or implementing data patterns.

Database schema design, migrations, query optimization with SQL, Exposed ORM, Flyway. Use for database, migration, schema, sql, flyway tags. Provides migration patterns, validation commands, rollback strategies.

Design and implement database indexing strategies. Use when creating indexes, choosing index types, or optimizing index performance in PostgreSQL and MySQL.

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Comprehensive guide for database management patterns covering PostgreSQL and MongoDB including schema design, indexing, transactions, replication, and performance tuning

Comprehensive database management workflow that orchestrates database architecture, schema design, performance optimization, and data governance. Handles everything from database design and implementation to performance tuning, backup strategies, and data migration.

World-class expert database master covering PostgreSQL, MySQL, MongoDB, Redis, and database architecture. Use when designing schemas, optimizing queries, planning migrations, implementing caching strategies, or solving complex database challenges at production scale.

Database schema migration patterns for Aurora MySQL including reconciliation migrations, idempotent operations, and MySQL-specific gotchas.

Creates database migrations with proper schema changes, data migrations, and rollback support for various ORMs (Prisma, TypeORM, Alembic, etc.). Use when managing database schema changes.