3. Data, Science & AI

Provides geometric and strategic analysis tools for Go board positions and game strategy evaluation.

Batch-generates images via OpenAI Images API with random prompts and creates an index.html gallery.

Enables image generation and understanding using Google Gemini models through the Python google-genai SDK, supporting multiple model variants.

Enables on-demand discovery and execution of MCP tools through agent-based workflows, resolving tool availability and context issues.

Invokes Google Gemini models (3.5 Pro, 2.5 Pro, 2.5 Flash) via Python SDK for text generation, code, and reasoning tasks.

Provides video analysis, transcription, and content extraction using Google Gemini AI models via the Python google-genai SDK.

Converts text to speech using ElevenLabs TTS for accessibility and user interaction.

Collects web data via search, organizes into JSON, and validates image URLs to prevent 404 errors.

Provides production best practices for building AI agents with Vercel AI SDK v5, covering security, performance, and deployment patterns.

Compares and selects the best algorithm from multiple options, optimizing performance for specific use cases.

Provides production-ready TypeScript implementations of agentic design patterns for building AI agents using Vercel AI SDK v5, including reflection, routing, and multi-agent patterns.

Manages service-scoped data orchestration for search, data streams, and kernel systems using hybrid dispatch and progressive streaming patterns.

Stress-test engine for real-time data streams featuring payload generation, throughput monitoring, and D3 visualizations for performance analysis.

Creates LLM-based skills by analyzing documentation, codebases, and GitHub repositories for AI application development.

Validates database schemas, identifies missing indexes, and audits Prisma ORM patterns to optimize database health and performance.

Converts PDFs to Markdown format while extracting embedded images, including JPEG2000 to PNG conversion, using pypdf.

Executes MCTS expansion phase by generating child nodes via LLM-based world model for AI planning and decision-making.

Manages AI prompt templates with CRUD operations, import/export, and backup/restore capabilities for efficient LLM dataset handling.

Executes the UCB1-based selection phase of Monte Carlo Tree Search to navigate from root to a promising leaf node.

Creates technically validated time-series visualizations with mathematical overlays, trendlines, and artifact resolution for data analysis.

Executes the backpropagation phase in Monte Carlo Tree Search (MCTS) to update node statistics from leaf to root in AI decision trees.

Executes MCTS simulation phase using LLM as heuristic policy to evaluate nodes in decision-making processes.

Executes Monte Carlo Tree Search with LLM for systematic exploration and solution of complex problems in research, planning, and coding.

Defines the ISA-95 equipment hierarchy standard for IIoT asset modeling, from enterprise to sensor levels.