3. Data, Science & AI

Provides data quality validation rules, metrics, and acceptance criteria for Somali dialect classifier datasets, including duplicate detection and language filtering.

Securely queries SAP OData endpoints to retrieve and explore business data entities like BusinessPartner and SalesOrder.

Provides persistent memory storage for AI agents to retain user preferences, project context, and learned patterns across sessions using MCP Memory Server.

Creates and reviews CLAUDE.md configuration files for Claude Code, applying HumanLayer guidelines to optimize AI instruction design and avoid anti-patterns.

Reverse-engineered Gemini API for text/image generation, supporting image-to-image/text and multi-turn conversations with session management.

Optimizes and manages AI language model prompts for conciseness, accuracy, and effectiveness in educational contexts.

Manages AI language model evaluation benchmarks, including creation, issue resolution, debugging, and result analysis.

Analyzes discrepancies between AI language model outputs and Python code in evaluations, providing actionable insights to close the gap and optimize prompts.

Analyzes AI agent evaluation results to identify language gaps and generate actionable insights for improving stdlib and prompt engineering.

Checks and processes messages from autonomous AI agents, enabling session management and handoff coordination in AI workflows.

Manages AI model evaluation by testing, validating, and adding models to the suite, including access checks, pricing, and models.yml updates.

Automates post-release evaluation for AILANG, running benchmark suites and updating dashboards with validation and progress reporting.

Generates AI-powered images from text or existing images, supports batch processing, image hosting, and long image merging for creative projects.

Validates correctness of sports science algorithms including VDOT, TSS, TRIMP, FTP, VO2max, Recovery, and Nutrition metrics.

Manages Linear session tracking to maintain persistent memory and context across AI conversation sessions.

Queries and synthesizes multi-level memory data to provide personalized, source-cited responses based on user history.

Extracts and converts web page content to clean markdown for efficient data retrieval and analysis.

Automates recording of key conversational information into hierarchical memory layers (situational, behavioral, cognitive, core) for AI-driven personal memory management.

Analyzes monthly behavioral patterns to refine cognitive frameworks and assess core beliefs using AI-driven insights for personal memory systems.

Analyzes weekly personal memory records to identify recurring behaviors, distill patterns into actionable insights, and update behavior layers upon user confirmation.

Provides authoritative YAML templates and scaffolding scripts for creating, reviewing, and managing agent system prompts and structures.

Enables creation, editing, and analysis of spreadsheets with formula support, formatting, and data visualization for structured data tasks.

Provides a CLI for training task-specific small language models, including data preparation, model training, and deployment.

Enables development of machine learning solutions using SAP HANA's in-database machine learning capabilities via the Python hana-ml library.