3. Data, Science & AI

Packages code repositories into AI-optimized files with customizable patterns, preserving structure for efficient AI analysis and documentation.

Manages Model Context Protocol (MCP) servers for discovering, analyzing, and executing AI tools and resources programmatically.

Processes and generates multimedia content including audio, images, video, and documents using Google Gemini API for advanced vision and audio capabilities.

Provides documentation and assistance for building AI agents, tools, and structured outputs with Pydantic AI framework.

Persistent graph-based memory system for AI agents using KIP, enabling retrieval, storage, and schema management of conversational and user data.

Analyzes conversation transcripts to extract user corrections, patterns, and preferences, then proposes skill improvements for enhanced performance.

Searches Atris journal history for past work, decisions, and patterns using grep-first, reason-second methodology.

Enables AI agents to reflect on their reasoning processes, improving output quality when starting tasks, feeling stuck, or before complex work.

Routes user requests to consult external LLM services such as Gemini and Codex for AI-driven answers.

Classifies task complexity (1-10) to route to the optimal AI model, ensuring efficient resource allocation and appropriate execution approach.

Provides optimal usage patterns for MiniMax MCP tools, specifically for web search and image understanding tasks.

Queries vault data using grep to extract frontmatter for projects, clients, tasks, and daily notes without full file reads.

Generates images, videos, and audio via fal.ai's serverless AI platform for real-time AI media features and editing.

Enables building and orchestrating LLM applications with LangChain, LangGraph, and RAG pipelines for advanced AI workflows.

Accesses Jewish calendar data, Shabbat times, and holidays through the Hebcal API for application integration.

Builds model-agnostic AI agents using Strands Agents SDK on AWS, supporting ReAct patterns and multi-agent systems for production deployment.

Creates data visualization dashboards with charts, KPIs, and metrics using Recharts for analytics reporting.

Fetches and displays trending GitHub repositories and developers for dashboard integration and trend analysis.

Enables building AI agents on AWS Bedrock AgentCore with tool integration, agent orchestration, and Bedrock model utilization.

Creates optimized system prompts and agent definitions using research-backed prompt engineering for enhanced LLM performance and structured documentation.

Provides access to extracted knowledge from winning Kaggle competition solutions across data science domains including NLP, computer vision, and time series.

Creates persistent memory storage for AI agents in the Elroy framework.

Ingests and processes documents into Elroy's memory system for AI-driven information retrieval and analysis.

Searches stored memories within the Elroy system for contextual information retrieval in AI workflows.