3. Data, Science & AI

Analyzes AI agent sessions (Maestro) via Braintrust for model evaluation and performance insights.

Provides unified mathematical computation, problem solving, and explanations by routing to appropriate tools.

Performs geometric operations including shape creation, boolean set operations, and spatial measurements using the Shapely library.

Provides step-by-step strategies for solving eigenvalue problems in linear algebra, including calculation methods and applications.

Provides mathematical strategies for solving boundary value problems in ordinary and partial differential equations, applicable in engineering and physics simulations.

Enables AI agents to retrieve and utilize previous reasoning steps and decisions to inform current problem-solving and decision-making processes.

Provides step-by-step strategies for solving problems in ring theory, including ideal theory and homomorphisms.

Enables AI-driven NPC navigation and decision-making using steering behaviors and NavigationServer in game development.

Generates unambiguous, reliable prompts for Agentica and REPL agents to ensure precise LLM task execution and avoid instruction errors.

Optimizes JUDO query performance by diagnosing slow queries, improving join strategies, and tuning expression evaluation for efficient database operations.

Translates JUDO query model to SQL for logical queries, expression-to-feature conversion, and debugging query generation in data applications.

Configures project with MCPs, rules, and agents in one command for AI agent development.

Offers problem-solving strategies for analytic functions in complex analysis, supporting mathematical computations and proofs.

Processes ocean data including statistical analysis, visualization, and report generation to prepare datasets for model training.

Provides problem-solving strategies for gradient-based optimization methods used in machine learning and AI model training.

Assesses clinical trial probability of success for regulatory approval using Bayesian statistical methods, updating prior evidence with trial data.

Provides fast, cost-effective AI processing for document analysis, image interpretation, and content summarization using Gemini Flash's large context window.

Queries Google NotebookLM notebooks for source-grounded, citation-backed answers using document-based responses to minimize hallucinations.

Converts session insights into reusable AI capabilities including skills, rules, and agents for continuous system enhancement.

Provides tools for implementing game AI systems including pathfinding, behavior trees, state machines, and combat logic for NPCs and autonomous characters.

Quantitative portfolio management tool for systematic risk management, including position sizing, correlation analysis, and gross/net exposure control based on Jim Simons' principles.

Aggregates health, work, wealth, and schedule data to deliver AI-driven insights via Google Gemini.

Provides physics system implementations for game development, including rigid bodies, collision detection, and raycasting.

Enables RAGAI Book Backend API integration into Docusaurus, including chat widget setup and backend configuration for AI-powered documentation.