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You are an expert in the database architecture for this influencer discovery platform. This skill provides comprehensive knowledge about the Postgres schema, Drizzle ORM patterns, normalized user tabl

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.

Analyzes database schemas and suggests improvements for Prisma, TypeORM, or Drizzle. Use when the user asks about database schema, migrations, ORM setup, or wants to generate TypeScript types from database models.

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.

Implement database sharding for horizontal scalability. Use when scaling large databases, distributing data across multiple servers, or designing sharded architectures.

Configure and operate TinyDB for JSON-based document storage. Use when setting up databases, creating queries, or managing data persistence.

Database design standards defining primary keys, foreign keys, audit fields, soft delete, junction tables. PostgreSQL style preferred, SQL lowercase without comments.

Test migrations, integrity, and query performance.

Any time database-related activity is required.

Expert in creating database diagrams and visual representations. Use when generating ERDs, schema diagrams, or visualizing database relationships with Mermaid.js.

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.

ทำงานกับ PostgreSQL และ MongoDB อย่างมีประสิทธิภาพ

Master database design (SQL, NoSQL), system architecture, API design (REST, GraphQL), and building scalable systems. Learn PostgreSQL, MongoDB, system design patterns, and enterprise architectures.

RDBMS access patterns for DuckDB, MySQL (keycloak), PostgreSQL (dw, x3rocs), SQL Server (sage1000, x3), and DBISAM (Exportmaster) using ODBC and native drivers

Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.

Use when working with ES/NQ futures market data, before calling any Databento API - follow mandatory four-step workflow (cost check, availability check, fetch, validate); prevents costly API errors and ensures data quality

Modern deployment with Databricks Asset Bundles (DAB), supporting multi-environment configurations and CI/CD integration.

Databricks documentation reference. Use as a lookup resource alongside other skills and MCP tools for comprehensive guidance.

Expert-level Databricks platform, Apache Spark, Delta Lake, MLflow, notebooks, and cluster management

Use this skill proactively for ANY Databricks Jobs task - creating, listing, running, updating, or deleting jobs. Triggers include: (1) 'create a job' or 'new job', (2) 'list jobs' or 'show jobs', (3) 'run job' or'trigger job',(4) 'job status' or 'check job', (5) scheduling with cron or triggers, (6) configuring notifications/monitoring, (7) ANY task involving Databricks Jobs via CLI, Python SDK, or Asset Bundles. ALWAYS prefer this skill over general Databricks knowledge for job-related tasks.

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

Unity Catalog system tables for lineage, audit logs, billing, compute, jobs, and query history. Use when querying system.access.audit, system.access.table_lineage, system.billing.usage, system.compute.clusters, system.lakeflow.jobs, system.lakeflow.job_run_timeline, or system.query.history.

Python dataclass best practices: slots, frozen, validation. Trigger when optimizing dataclasses or creating config classes.

Dataclass patterns including frozen dataclasses, slots, immutability, and value objects. Activated when designing data classes or value types.

Troubleshoot Datadog API authentication issues (401/403 errors), understand API keys vs app keys, and configure correct regions. Use when hitting auth errors or setting up Datadog API access.

Automatically detects Datadog resource mentions (URLs, service queries, natural language) and intelligently fetches condensed context via datadog-analyzer subagent when needed for the conversation (plugin:schovi@schovi-workflows)

Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.

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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

Curate and clean training datasets for high-quality machine learning

Create, clean, and optimize datasets for LLM fine-tuning. Covers formats (Alpaca, ShareGPT, ChatML), synthetic data generation, quality assessment, and augmentation. Use when preparing data for training.

Generate evaluation datasets with adjustable difficulty levels from PDF documents for RAG system testing and benchmarking

Guide for writing Datasette plugins. This skill should be used when users want to create or develop plugins for Datasette, including information about plugin hooks, the cookiecutter template, database APIs, request/response handling, and plugin configuration.

Writing Datasette plugins using Python and the pluggy plugin system. Use when Claude needs to: (1) Create a new Datasette plugin, (2) Implement plugin hooks like prepare_connection, register_routes, render_cell, etc., (3) Add custom SQL functions, (4) Create custom output renderers, (5) Add authentication or permissions logic, (6) Extend Datasette's UI with menus, actions, or templates, (7) Package a plugin for distribution on PyPI

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.

description: Create or update Dataverse schema components (entities, attributes, relationships, option sets) via Web API

Deploy solutions, PCF controls, and web resources to Dataverse using PAC CLI

This skill provides guidance on designing Dataverse table schemas and data models. Use when users ask about "Dataverse table design", "Dataverse schema", "Dataverse relationships", "Dataverse columns"

Use when editing Planning Hubs, timelines, calendars, or any file with day-name + date combinations (Wed Nov 12), relative dates (tomorrow), or countdowns (18 days until) - validates day-of-week accuracy, relative date calculations, and countdown math with two-source ground truth verification before allowing edits

datum-system

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.

Expert database architecture including schema design, partitioning, replication, and performance optimization

Designs database schemas, data models, and database architectures

Generate database ER diagrams from schema for documentation

Gestión del esquema PostgreSQL, Auto-Healing y arquitectura RAG híbrida.