3. Data, Science & AI

Generates professional images using Google's Gemini 3 Pro AI model for creative visual content.

Provides foundational principles for AI-powered development workflows, including TRUST 5, SPEC-First TDD, token optimization, and modular architecture.

Manages enterprise context and session state with token budget optimization for efficient AI application performance.

ATF enables AI systems to navigate large documentation files by accessing only relevant sections, optimizing token usage for efficient processing.

Analyzes GLOW master data schemas and CSV files using SQL with DuckDB and jq for structured data exploration.

Validates master data CSV files for database compatibility and alignment with server/client implementation by cross-referencing templates and DB schema.

Generates release-key-based reports for GLOW master data with table-specific CSV, statistical JSON, and DuckDB query support for flexible analysis.

Manually triggers external AI analysis to uncover blind spots in business or technical processes.

Converts PDF, DOCX, and audio files into structured LLM-ready knowledge for AI applications, enabling quick data ingestion and retrieval.

Unified API proxy for multiple AI providers with automatic rotation, streaming support, and zero vendor lock-in.

Comprehensive AI context engineering suite enabling observability, structured outputs, and hybrid memory for enhanced RAG and LLM applications.

Optimizes context handling for autonomous AI agents using advanced curation patterns like Nvidia Eureka and Context Hygiene.

Framework enabling deterministic workflows for AI agents, moving beyond probabilistic models to ensure reliable and predictable outcomes.

Provides task delegation patterns for multi-agent systems, including hierarchical, parallel, and reactive approaches.

Advanced prompt engineering techniques for AI models, covering context engineering, DSPy framework, token optimization, and security measures.

Provides a standardized system for indexing, querying, and retrieving knowledge from external sources including URLs, databases, and documentation.

Provides genetic algorithms for AI model optimization, including hyperparameter tuning and evolutionary strategies.

Manages Supabase database operations including schema migrations, RLS policies, security audits, and performance optimization using best practices.

Creates and manages user-defined rules to customize AI behavior, enabling personalized interactions and control over AI responses.

Step-by-step guide for defining agent personas, generating system prompts, and assembling specialized agent workflows.

Transforms and maps data between pipeline stages (Miner to Appraiser) for seamless data flow in data processing workflows.

Provides evolutionary and parametric optimization using Fibonacci sequence and the Golden Ratio for scientific applications.

Scrapes product data from provider websites and updates the market database for real-time market insights.

Technical guide for implementing correct Claude-style tool calling patterns, syntax, and examples in AI agent development.