Explore and analyze pilot data sets to uncover patterns, anomalies, and initial insights. Use when performing ad-hoc data investigations, validating data quality, or preparing exploratory visualizations for hypothesis generation.

Data governance strategy, quality validation rules, and data dictionary management for vehicle insurance platform. Use when defining data quality standards, implementing validation rules, managing field mappings, resolving data conflicts, or establishing data governance processes. Covers data cleaning standards, quality metrics, and mapping management.

Procedures and playbooks for responding to data quality incidents, data loss, corruption, and pipeline failures.

Build new data ingestion providers following the FF Analytics registry pattern. This skill should be used when adding new data sources (APIs, files, databases) to the data pipeline. Guides through creating provider packages, registry mappings, loader functions, storage integration, primary key tests, and sampling tools following established patterns.

Provides architectural guidance for data lake design including partitioning strategies, storage layout, schema design, and lakehouse patterns. Activates when users discuss data lake architecture, partitioning, or large-scale data organization.

Organize object storage with lifecycle policies.

Mapping the flow of data from source to destination for transparency, impact analysis, and troubleshooting.

Data mapping patterns for transforming API responses to internal types

Expert-level data mesh architecture, domain-oriented ownership, data products, federated governance, and self-serve platforms

You are a database migration expert specializing in safe schema changes and data migrations. Your goal is to ensure migrations are safe, reversible, and won't corrupt production data.

Create safe, reversible database migration scripts with rollback capabilities, data validation, and zero-downtime deployments. Use when changing database schemas, migrating data between systems, or performing large-scale data transformations.

발굴조사 자료(논문/보고서/주변유적) 수집 및 메타데이터 정규화

Build orchestration pipelines with idempotency.

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

Detect PII, mask data, and manage consent and encryption.

Data product design patterns with contracts, SLAs, and governance for building self-serve data platforms using Data Mesh principles.

Implement validation, profiling, and anomaly detection.

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.

- [Purpose](#purpose)

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.

Manage AI training data, monitor content freshness, detect repetition, and update training samples for continuous learning. Use when managing training data, checking content quality, updating AI models, or preventing repetitive content.

Build mathematically correct, visually prominent data visualizations for time-series charts. Use this skill when creating charts with mathematical overlays (trendlines, patterns, indicators), fixing visual artifacts (wavy lines, domain mismatches), or validating chart correctness. Focuses on technical correctness and progressive validation, not aesthetic design.

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.

Design dimensional models and fact tables.

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Automate backups, replication, and performance tuning.

database-administrator

'Use SQL (PostgreSQL) when:'

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

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

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Database design, optimization, and operations expert

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.

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

Plan zero-downtime migrations and rollback.

Database schema migration patterns and best practices. Use when creating database migrations, implementing zero-downtime schema changes, version control for databases, or managing data migrations.

| Atributo | Valor |

Resets local development database by deleting all data and restarting API container to trigger auto-seeding. SINGLE SOURCE OF TRUTH for dev database reset automation.

Expert guidance for designing, optimizing, and maintaining database schemas for SQL and NoSQL systems. Use when creating new databases, optimizing existing schemas, planning migrations, implementing security policies, or ensuring GDPR compliance. Covers normalization, indexing, data types, relationships, performance optimization, and audit logging.

Design robust, scalable database schemas for SQL and NoSQL databases. Provides normalization guidelines, indexing strategies, migration patterns, constraint design, and performance optimization. Ensures data integrity, query performance, and maintainable data models.

Document database schemas, ERD diagrams, table relationships, indexes, and constraints. Use when documenting database schema, creating ERD diagrams, or writing table documentation.

Extend the Supabase PostgreSQL database schema following this project's declarative schema patterns, migration workflow, and type generation pipeline. Use when adding tables, columns, enums, RLS policies, triggers, or database functions.

Generate ORM models, migrations, and seeds.

VaultCPA database schema reference with 50+ Prisma models, relationships, and query patterns. Use when working with database models, designing features, or understanding data structure.

Validates database schemas, Kysely types, and migrations. Use when checking schema correctness or migration safety.

Enforces project database schema conventions when creating or modifying Drizzle ORM table definitions, including constraints, indexes, relations, and column patterns. This skill should be used proactively whenever working with schema files to ensure consistent schema design for PostgreSQL with Neon serverless.