3. Data, Science & AI

Provides PostgreSQL database schema and migration scripts for the MuebleriaIris ERP system.

Extracts company details from Wanted.co.kr profile pages, including industry, contact, and company description.

Extracts text from PDF documents using multiple robust libraries, enabling text manipulation, search, and conversion for data processing workflows.

Extracts job posting details from Korean recruitment platforms including wanted.co.kr and saramin.co.kr.

API-based image generation using OpenAI and Google APIs, supporting text-to-image, reference images, and quality presets.

Provides intelligent decision-making for autonomous development tasks, including complexity assessment, execution mode selection, and failure recovery strategies.

Provides best practices and patterns for implementing vector search with LanceDB, a vector database for AI/ML applications.

Creates new AI agent skills adhering to the Agent Skills specification, enabling custom capability development for AI agents.

Guides schema design, indexing strategies, ORM selection, and serverless database considerations for efficient data management and performance.

Automates specialist agent selection for user requests via AI analysis, eliminating explicit agent mentions.

Provides guidance on interacting with the OmniForge Memory Server, including SQL patterns, connection methods, and security auditing best practices for database management.

Standard reference for business working day (4am-4am) to handle date filtering, reports, and time-based data queries.

Provides Python machine learning coding patterns to identify and avoid common pitfalls, ensuring adherence to best practices.

Enterprise Google Sheets automation with AI-powered data analysis, transformation, and reporting via compliant MCP server.

Manages local episodic thread memory for AI agents, handling data ingestion, state updates, and vector-indexed belief storage.

Specialized tool for extracting, cleaning, and analyzing structured data from CSV, JSON, and Markdown tables.

Provides expert guidance on SQL optimization, MyBatis XML mapping, and schema design for MySQL databases.

Extracts structured data from markdown feature proposals for seamless integration into data systems and analysis workflows.

Quick reference guide for optimizing MySQL database performance through schema design, indexing, and security patterns.

Converts FAQ documents (XLSX, Word, PDF, TXT) into RAG-optimized formats for efficient AI knowledge base integration.

Batch-generates images via OpenAI Images API with random prompts and outputs an HTML gallery.

Optimizes AI prompts through six-dimensional quality assessment (Clarity, Efficiency, Structure, Completeness, Actionability, Specificity) to enhance model performance.

Enables direct SQL query execution and data manipulation for Supabase PostgreSQL databases, supporting standard CRUD operations.

Creates and maintains AI agent context notes for development, debugging, and project exploration, stored in git-ignored directories for agent-specific use.