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.

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.

data-visualizer

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.

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

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.

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.

Expert database optimizer specializing in modern performance

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.

Test migrations, integrity, and query performance.

Any time database-related activity is required.

Language-agnostic database best practices covering migrations, schema design, ORM patterns, query optimization, and testing strategies. Activate when working with database files, migrations, schema changes, SQL, ORM code, database tests, or when user mentions migrations, schema design, SQL optimization, NoSQL, database patterns, or connection pooling.

Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.

Kailash DataFlow - zero-config database framework with automatic model-to-node generation. Use when asking about 'database operations', 'DataFlow', 'database models', 'CRUD operations', 'bulk operations', 'database queries', 'database migrations', 'multi-tenancy', 'multi-instance', 'database transactions', 'PostgreSQL', 'MySQL', 'SQLite', 'MongoDB', 'pgvector', 'vector search', 'document database', 'RAG', 'semantic search', 'existing database', 'database performance', 'database deployment', 'database testing', or 'TDD with databases'. DataFlow is NOT an ORM - it generates 11 workflow nodes per SQL model, 8 nodes for MongoDB, and 3 nodes for vector operations.

Use when developing BigQuery Dataform transformations, SQLX files, source declarations, or troubleshooting pipelines - enforces TDD workflow (tests first), ALWAYS use ${ref()} never hardcoded table paths, comprehensive columns:{} documentation, safety practices (--schema-suffix dev, --dry-run), proper ref() syntax, .sqlx for new declarations, no schema config in operations/tests, and architecture patterns that prevent technical debt under time pressure

Extracts key specifications from component datasheet PDFs for maker projects. Use when user shares a datasheet PDF URL, asks about component specs, needs pin assignments, I2C addresses, timing requirements, or register maps. Downloads and parses PDF to extract essentials. Complements datasheet-parser for quick lookups.

DAW-specific quirks, known issues, and workarounds for Logic Pro, Ableton Live, Pro Tools, Cubase, Reaper, FL Studio, Bitwig with format-specific requirements (AU/VST3/AAX). Use when troubleshooting DAW compatibility, fixing host-specific bugs, implementing DAW workarounds, passing auval validation, or debugging automation issues.

This skill should be used when seeding databases with realistic fake data for development, testing, or staging environments. Supports PostgreSQL, MySQL, SQLite, MongoDB with ORM-based seeding (SQLAlchemy, Django, Prisma) and Faker library for generating realistic test data. Use when the user needs to populate databases with sample data, create test fixtures, or set up development/staging environments with realistic data.

SQLite database management with Prisma ORM, type-safe queries, and Railway deployment with Litestream backup. This skill should be used when creating database schemas, writing migrations, managing SQLite on Railway volumes, or troubleshooting database issues.

Complete guide for dbt data transformation including models, tests, documentation, incremental builds, macros, packages, and production workflows

PROACTIVE skill - STOP and invoke BEFORE writing dbt SQL. Validates models against coding conventions for staging, integration, and warehouse layers. Covers naming, SQL structure, field conventions, testing, and documentation. CRITICAL - When about to write .sql files in models/, invoke this skill first, write second. Supports project-specific convention overrides and sqlfluff integration.

Create dbt models following FF Analytics Kimball patterns and 2×2 stat model. This skill should be used when creating staging models, core facts/dimensions, or analytical marts. Guides through model creation with proper grain, tests, External Parquet configuration, and per-model YAML documentation using dbt 1.10+ syntax.

Comprehensive guide to dbt (data build tool) patterns, modeling best practices, testing strategies, and production workflows for modern data transformation

Transform AI agents into experts on dbt and Snowflake performance optimization, providing guidance

Provides expert-level assistance with dbt Semantic Layer, MetricFlow, semantic models, metrics, dimensions, entities, measures, and BI tool integrations. Use this skill when building semantic models, creating metrics (simple, ratio, cumulative, derived, conversion), debugging validation errors, or integrating with BI tools. Extracted from official dbt documentation and optimized for data practitioners.

ALWAYS USE when working with dbt models, SQL transformations, tests, snapshots, or macros. Use IMMEDIATELY when editing dbt_project.yml, profiles.yml, or creating SQL models. MUST be loaded before any transform-layer work. Enforces dbt owns SQL principle - never parse, validate, or transform SQL in Python.

Créer des tests exhaustifs pour les bounded contexts DDD suivant une approche TDD (Test-Driven Development) avec des standards de coverage stricts.

Conduct authorized denial of service testing to assess network resilience and configure intrusion detection systems (IDS) to detect and alert on various DoS attack patterns. This skill covers volume-b

End-to-end associate workflow with time-boxed gates: thesis -> sourcing -> meetings -> diligence -> memo, ending with either IC-ready memo or explicit kill decision. Use when you need to run the full pipeline for a sector or a specific deal.

Wind/Wall/Door multi-perspective debate orchestration using debate-hall-mcp tools. Use when facilitating structured debates, architectural decisions, or multi-perspective analysis.

Start structured red vs. blue team debates via subagents. Use when exploring a topic from multiple adversarial perspectives.

Structured multi-perspective debate for important architectural decisions and complex trade-offs

Use when users need to debug, modify, or extend the code-forge application's CLI commands, argument parsing, or CLI behavior. This includes adding new commands, fixing CLI bugs, updating command options, or troubleshooting CLI-related issues.

Universal PDCA debugging framework for systematic hypothesis verification. Use when debugging issues that require structured investigation, observing runtime behavior, or verifying fixes through iterative testing.

Debug FFmpeg integration and video/audio processing issues. Use when the user encounters FFmpeg errors, audio extraction problems, codec issues, or video processing failures.

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Document debugging sessions with hypothesis tracking and knowledge base

Systematic debugging workflow with hypothesis testing

Debug and diagnose Thread mesh networks and OpenThread Border Routers. Use when troubleshooting Thread connectivity, analyzing Router Advertisements, testing IPv6 reachability to Thread devices, inspecting Thread Network Data, or diagnosing Border Router configuration issues.

Deploy to the production VPS (archivist@194.163.189.144) and iteratively debug failures until successful deployment.

Debug crashes, segfaults, and memory errors using valgrind integration with nextest through pre-configured profiles

Guides developers through scenario test debugging using Ruby debug gem step execution. Provides interactive debugging patterns and test helper context.

Systematic bug investigation and resolution workflow with root cause analysis.

Expert at advanced debugging and root cause analysis. Use when troubleshooting complex issues, finding root causes of bugs, investigating performance problems, or analyzing system failures.

Debugs Docker build failures, container runtime errors, platform architecture issues (ARM64/AMD64/WSL2), AWS ECR/ECS pull failures, and optimizes Docker workflows. Use when encountering Docker build errors, container crashes, ECR authentication issues, ECS deployment problems, performance issues, networking failures, volume permission errors, or when working with multi-platform Docker images.