3. Data, Science & AI

Analyzes datasets and creates visualizations for data-driven insights and decision-making.

Curates AI-focused newsletter content with automated deduplication and ranking to deliver relevant, non-redundant updates.

Expert for writing quantitative trading indicators and technical analysis scripts in Navi Stream DSL, optimized for real-time market data processing and financial computations.

Reference guide for generating images using Google GenAI library with gemini-3-pro-image-preview model, covering API patterns and best practices.

Generates safe, read-only PostgreSQL queries from natural language for data retrieval across specified databases, including result analysis with confidence scoring.

Enables parallel execution of AI tasks across multiple providers and intelligent consolidation of results for higher-quality outputs.

Guide for building production AI chatbots with ChatKit, OpenAI Agents SDK, and custom backends, enabling real-time task execution and user isolation.

Builds semantic vector search systems for document retrieval, RAG applications, and knowledge bases using AgentDB.

Enables adaptive learning systems for pattern recognition, strategy optimization, and continuous improvement in self-learning agents and meta-cognitive systems.

Enables efficient semantic search and nearest neighbor queries via vector databases for optimized information retrieval.

Assists end-users with Snowflake access requests, RSA key generation, and connection setup for basic data platform usage.

Expert SQL query writing, optimization, and database schema design for PostgreSQL, MySQL, SQLite, and SQL Server, including complex queries and performance tuning.

Combines vector and keyword search to improve retrieval accuracy in RAG systems and search engines.

Provides standardized prompt engineering and context engineering principles for AI agents, optimized for clarity, structure, and signal-to-noise ratio based on Anthropic best practices.

Enables dynamic multi-agent coordination through self-organizing swarm patterns and topology adaptation for AI system design.

Integrates Replicate AI models with background processing, S3 storage, and credit systems for scalable AI application deployment.

Queries structured data from Obsidian bases using the Bases Query plugin via RPC, enabling efficient data retrieval for knowledge management.

Analyzes EDN templates in Logseq databases for structure, quality, orphaned items, and version comparison to optimize template usage.

Displays Claude Router usage statistics and cost savings insights for resource and financial analysis.

Downloads and processes YouTube video transcripts for subtitle extraction, video summarization, and content analysis.

Creates data pipeline projects with SQL and Python models, including DAG definitions and project structure setup.

Provides detailed guidance on constructing a Retrieval Augmented Generation (RAG) pipeline, covering data ingestion and vector search implementation.

Enables ethical evaluation of AI systems, including bias detection, fairness implementation, and alignment with human values.

Provides receipt scanning and database integration for nonprofit finance tracking, utilizing OCR for automated data extraction and storage.