3. Data, Science & AI

Protocol for discovering and coordinating AI agents across federated communication channels, enabling decentralized multi-agent collaboration.

Coordinates multiple AI agents across channels, manages sessions, distributes tasks, and utilizes distributed compute resources.

Enables creation, editing, and analysis of spreadsheets including formulas, formatting, and data visualization for data processing tasks.

Analyzes and rewrites user prompts to maximize LLM response quality and effectiveness through strategic optimization.

Optimizes generative AI engine performance for search engines like ChatGPT, Claude, and Perplexity to enhance response quality and relevance.

Adapts AI behavior across operational modes including brainstorm, implement, debug, and orchestrate for optimized task execution.

Enables seamless integration of OpenAI API for chatbots, content generation, and AI-powered educational applications.

Executes AI code tasks across multiple backends (Codex, Claude, Gemini) with file references and structured output.

Formats structured data (tables, logs, analytics) into TOON v2.0 for AI/ML pipelines, supporting multiple array types and delimiters.

Builds AI agents with Google's Agent Development Kit (ADK) in Python, supporting tool integration, multi-agent systems, and Vertex AI deployment.

Optimizes prompts for AI models including LLMs and image generators, covering structure, style, and iterative refinement for marketing, code, and creative domains.

Comprehensive platform for proteomics data analysis, supporting feature detection, peptide identification, and protein quantification in mass spectrometry workflows.

Accesses European Nucleotide Archive to retrieve DNA/RNA sequences, FASTQ files, and genome assemblies for bioinformatics analysis.

Enables querying global statistical data including demographics, economics, health, and environmental metrics via Data Commons API.

Optimizes context window management and token usage for large language models, reducing computational costs while maintaining session integrity.

Organizes PyTorch code into LightningModules for scalable neural network training with distributed computing and logging.

Queries ChEMBL database for bioactive molecules, enabling structure-based searches and bioactivity data retrieval for medicinal chemistry research.

Provides numerical computing capabilities for matrix operations, data analysis, visualization, and scientific computing in MATLAB and GNU Octave.

Phylogenetic tree toolkit for manipulation, evolutionary event detection, and visualization in phylogenomics research.

Accesses BRENDA enzyme database via SOAP API to retrieve kinetic parameters, reaction equations, and organism data for biochemical research.

Statistical visualization library for exploratory data analysis, with pandas integration and default styles for distributions, relationships, and categorical plots.

Comprehensive toolkit for computational materials science, handling crystal structures, phase diagrams, band structure, DOS, and Materials Project integration.

Integrates with protocols.io API to manage scientific protocols, including creation, updates, steps, materials, and collaborative workflows for lab documentation and experiment tracking.

Provides differential gene expression analysis for RNA-seq data using DESeq2, including Wald tests, FDR correction, and volcano/MA plots.