3. Data, Science & AI

Python toolkit for molecular biology data processing, including sequence analysis, file parsing, and programmatic access to biological databases.

Provides structured memory architecture for AI agents, including working, short-term, long-term, and temporal knowledge graphs.

Enables querying COSMIC database for cancer mutations, gene fusions, and genomic data to advance cancer research and precision oncology.

High-performance in-memory DataFrame library with lazy evaluation and Apache Arrow backend for fast data processing and ETL pipelines.

Interactive visualization library for creating web-based charts with hover, zoom, and pan features, ideal for data dashboards and exploratory analysis.

Dispatches independent AI agents to solve parallel problem domains without shared state or sequential dependencies.

Detects and reports system resources (CPU, GPU, memory, disk) to inform optimal computational strategies for scientific tasks.

Generates evidence-based clinical decision support documents with biomarker-stratified cohort analyses and statistical reports for pharmaceutical research.

Enables distributed computing for pandas and NumPy workflows, scaling beyond memory limits for parallel processing and distributed machine learning.

Provides evaluation methodologies for AI agents using LLM-as-judge, rubrics, and quality gates to measure performance and quality.

Provides access to Human Metabolome Database for searching metabolites, retrieving chemical properties, spectra, and pathways to support metabolomics research and compound identification.

Cloud-based quantum chemistry platform for molecular property prediction, protein docking, and AI-driven simulations via Python API.

Generates publication-ready scientific diagrams with AI-driven refinement for neural networks, biological pathways, and complex system visualizations.

Provides access to NCBI GEO database for searching, downloading, and retrieving gene expression datasets including microarray and RNA-seq data in SOFT and Matrix formats.

Queries Reactome REST API for systems biology analysis, including pathway mapping, gene interactions, and disease-related studies.

Fetches pre-optimized documentation for Stripe, designed for seamless integration with large language models and RAG systems.

Enables AI agents to store and query persistent long-term memory of past work, patterns, and learnings.

Automates context compression in AI model interactions to maintain performance when context size exceeds thresholds, preventing slowdowns.

Automatically selects between Claude Opus and Sonnet models based on task complexity to optimize cost and quality.

Retrieves Google Forms responses for data analysis and reporting.

Generates new sub-agents with specific roles for AI agent workflows within plugin systems.

Analyzes repositories for AI agent readiness using a 10-pillar framework, providing maturity assessment and configuration guidance.

Enables TNF agents to leverage Clawdbot's AI skills and system access via Cloud Sandbox for persistent assistance.

Automates audio-to-sheet-music conversion and compiles professional songbooks for musicians.