3. Data, Science & AI

Analyzes SQLite query patterns using machine learning to recommend performance-optimized SQL approaches for database efficiency.

Performs exploratory data analysis on tabular datasets, including distribution checks, missing data analysis, correlation computation, and data quality reporting.

Converts Nextflow subworkflows to Galaxy workflow format for seamless integration in bioinformatics data analysis pipelines.

Converts Nextflow pipelines to Galaxy workflows for reproducible data analysis in bioinformatics and scientific research.

Manages YouTube video caching with semantic search via Qdrant, automatically verifying and providing metadata and transcripts on request.

Creates and optimizes prompts for LLMs to improve output quality and design production-ready templates for agent interactions.

Routes Nextflow workflow definitions to corresponding Galaxy workflow conversions, enabling seamless transition between bioinformatics platforms.

Detects AI-generated writing patterns to verify content authenticity, aiding in auditing and publishing decisions.

Verifies data access, inspects table schemas, and checks row counts to understand dataset structure before analysis.

Generates anonymized social value reports from CSV inputs, processing data and producing month-by-month markdown summaries.

Analyzes CSV data and figures to automatically generate the Results section in a document, following a structured writer workflow.

Manages AI agent creation, validation, and enhancement through system prompt engineering and structural checks.

Indexes and searches project documents and chat history to retrieve prior work and context for new tasks efficiently.

Fetches YouTube video transcripts and subtitles using youtube-transcript-api for data analysis, summarization, and caption translation tasks.

Advises on session reuse or new session creation for multi-model AI collaboration, ensuring optimal context isolation before invoking models like Codex or Gemini.

Provides common patterns and best practices for coordinating multiple AI agents in collaborative systems.

Converts innovation PRDs into structured experiment plans with hypotheses, metrics, and evaluation methods for RAG, AI agents, and automation outcomes.

Coordinates multiple AI agents within a persistent system, enabling complex task execution through agent collaboration and state management.

Builds and deploys production-ready RAG chatbots with embedded text questioning and conversation history using Cohere, Qdrant, and FastAPI.

Proposes multi-agent and workflow architectures for CustomGPT.ai Labs projects, integrating Claude Code and CustomGPT.ai to achieve business outcomes.

Comprehensive Python AI/ML development expert for project setup, model training, data processing, RAG pipelines, and UV dependency management.

Enables RAG system integration with xAI Grok Collections and Google Gemini for AI chatbots with document-based knowledge context.

MongoDB CLI tool for executing queries, CRUD operations, aggregation pipelines, and index management with configurable output formats and production-safe read-only mode.

Generates markdown summary reports with statistical insights from candidate profile data in CSV format.