3. Data, Science & AI

Orchestrates workflows across multiple AI models for security research, competition execution, and strategic analysis via GUI or API automation.

Manages AI context engineering using a structured framework, enabling creation, validation, analysis, and updates of context files for AI systems.

Provides expert guidance for Apache NiFi data integration platform, including flow design, processors, and cluster configuration.

Forecasts project completion dates using Monte Carlo simulation with historical throughput data and optional confidence levels.

Provides probabilistic forecasts for story/task completion using Monte Carlo simulation based on historical throughput data.

Guides users on implementing Model Context Protocol (MCP) to connect external tools and extend Claude Code's AI capabilities.

Processes PDF documents for text extraction, content analysis, and data manipulation to enable structured data integration.

Guides selection between Anthropic's Sonnet and Haiku models based on task complexity to optimize cost and quality for AI agent workflows.

AI system analyzing 22 financial, life event, property, legal, and market distress signals to identify distressed property leads and optimize conversion through self-improvement and A/B testing.

AI system autonomously optimizing distressed property lead generation via performance monitoring, bottleneck resolution, and A/B testing to maximize conversion rates.

Detects structural breaks and segments time-series data using statistical methods for financial market analysis.

Unified logging system capturing AI orchestration workflow states and execution logs in a single file for efficient monitoring and debugging.

Assigns the database architect role to Claude Agent, enabling data-focused design and optimization capabilities.

Implements attention-based trading models with LSTM, cross-attention, and interpretable predictions for trend-following strategies.

Provides tools for financial time-series analysis including returns calculation, volatility targeting, momentum indicators, and portfolio construction for trend-following strategies.

Generates actionable business insights, visualizations, and executive reports from data model outputs, identifying gaps and suggesting feature improvements.

Enables rapid financial model adaptation using few-shot learning, meta-learning, and transfer learning across market regimes.

Manages text cleaning pipelines via REPL interface, enabling input configuration and data processing through socket server.

Automates content discovery from academic/code repositories using AI filtering, deduplication, and quality analysis, then publishes to multiple channels.

Orchestrates quality assurance by refining outputs from other skills through standards-based evaluation and iterative improvement processes.

Orchestrates end-to-end generation and validation of experimental procedures from LA-Bench data, including parsing and 10-point scoring.

Validates experimental procedures against LA-Bench standards using formal and semantic evaluation to ensure compliance before submission.

Calculates ISS orbital positions and validates tracking accuracy using TLE data and SGP4 propagation algorithms.

Fetches web content, extracts specific topics via AI subagents, and saves structured markdown summaries for documentation analysis.