3. Data, Science & AI

Orchestrates concurrent execution of multiple AI agents for parallel implementation of tasks and phases.

Creates and manages modular PostgreSQL workspaces for structured database development and module organization.

Dispatches multiple AI agents in parallel to solve independent tasks without shared state or sequential dependencies.

Enables local LLM inference in TypeScript applications using Ollama, supporting text generation and AI workflows without cloud dependencies.

Enables semantic similarity search using pgvector in PostgreSQL for RAG pipelines and document retrieval tasks.

Builds end-to-end RAG pipelines integrating vector search (pgvector) with LLM generation (Ollama) for document Q&A and AI search applications.

Runs parallel AI critique agents to verify complex work and achieve consensus through multi-agent collaboration.

Sets up pgvector extension in PostgreSQL for vector storage, enabling semantic search and RAG application development.

Enables creation and editing of BMAD agents, workflows, and modules within the BMAD builder environment.

Configures agentic-kit for RAG using pgvector and PGPM, enabling contextual AI responses from a knowledge base.

Delegates AI tasks to isolated Claude agents within Buddy Sandbox environments for secure and parallel execution of complex workflows.

Assists in MongoDB database exploration, querying, and debugging with MCP tools for aggregation pipelines and schema analysis.

Generates database migration files (deploy/revert/verify) using pgpm for safe schema changes like adding tables or functions.

Loads MACS controller prompt to supervise a worker agent in a separate terminal window.

Creates and refines AI agent skills per agentskills.io specification for building agent-based automation workflows.

Enables manual creation of database savepoints for granular transaction rollback during complex data operations.

Optimizes MongoDB query performance for Viya services by diagnosing N+1 issues and validating index usage with explain.

Provides understanding of core logistics data entities and their relationships in Viya TMS for effective shipping data modeling and feature development.

Guides on OpenCode features, configuration, and troubleshooting for AI automation within the repository.

Reverts database transactions to a designated savepoint for precise transaction control in SQL environments.

Scrapes Taiwan Government E-Procurement tender listings for local filtering and analysis to source procurement opportunities.

Displays a list of database savepoints for transaction management and debugging purposes.

Analyzes MyBatis SQL queries and provides optimization recommendations to improve database performance.

Guides AI agents through self-evolution initialization by processing AGENT_INIT.md documentation upon user trigger phrases.