Access comprehensive enzyme kinetic data from the worlds largest enzyme database. Find Km values, reaction equations, organism-specific parameters, and substrate specificity data for biochemical research and metabolic engineering.

Query 40+ biological databases including UniProt, KEGG, and ChEMBL with a consistent Python API. Simplifies cross-database analysis and identifier conversion for bioinformatics research.

Researchers waste hours manually searching bioRxiv for relevant preprints. This skill automates literature discovery with precise filtering by keywords, authors, date ranges, and scientific categories.

Process DNA, RNA, and protein sequences efficiently using Biopython. Access NCBI databases programmatically, perform sequence alignments, and automate complex bioinformatics pipelines for research applications.

Biomni transforms complex biomedical research by autonomously executing multi-step analysis tasks. Researchers can focus on scientific questions while AI handles data processing, literature review, and computational analysis across genomics, drug discovery, and clinical domains.

Automate laboratory workflows and manage biological data by integrating with the Benchling R&D platform. Access DNA sequences, protein data, inventory, and electronic lab notebooks through the Python SDK or REST API.

Working with astronomical data requires handling complex coordinate systems, file formats, and calculations. This skill provides guidance for using Astropy to process celestial coordinates, FITS files, and cosmological computations.

Gene regulatory network inference identifies transcription factor-target gene relationships from transcriptomics data. Arboreto provides scalable implementations of GRNBoost2 and GENIE3 algorithms that process both bulk and single-cell RNA-seq data on local machines or distributed clusters.

AnnData provides a standardized data structure for annotated matrices used in single-cell genomics. This skill enables creating, reading, writing, and manipulating .h5ad files with full support for metadata, embeddings, and the scverse ecosystem.

Researchers need efficient access to computational protein structure predictions for drug discovery and structural biology studies. This skill provides direct access to AlphaFold DB's 200M+ AI-predicted protein structures, enabling retrieval by UniProt ID, download of coordinate files, and analysis of confidence metrics.

Time series data requires specialized algorithms beyond standard machine learning. Aeon provides scikit-learn compatible APIs for classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search on temporal data.

Protein design requires experimental validation. Adaptyv provides API access to a cloud laboratory for automated testing of binding affinity, expression levels, thermostability, and enzyme activity. Get experimental results in approximately 21 days.

Creating engaging, educational picture books for children requires careful attention to visual consistency, age-appropriate content, and cultural relevance. This skill generates high-quality bilingual picture book content with 18 visual styles and 12 scene types, tailored for ages 3-12.

Publishing content to X requires manual typing or risky auto-posting tools. This skill uses browser automation to prepare tweets and save them to draft, ensuring full user review before any post goes live.

Content creators spend too much time deciding which topics to write about. This skill scores and filters collected materials using a 10-point weighted system based on trending, controversy, value, and relevance criteria, helping prioritize high-potential content.

Content creators struggle to consistently produce engaging social media posts. This skill generates viral X (Twitter) content including short tweets, multi-tweet threads, and replies using proven patterns tailored to your personal style.

Creating engaging X (Twitter) content requires thorough research across multiple sources. This skill automates a 4-round web search strategy to collect authoritative, technical, comparative, and verified materials for your posts.

AI memory files grow large and waste input tokens. This skill compresses natural language prose to caveman format, saving 65-75% of tokens while preserving all code, URLs, and technical content.

AI coding agents can produce long responses that cost tokens and money. This skill reads the Claude Code session log and shows exactly how many tokens caveman mode saved, with no AI estimation or guesswork.

AI coding agents produce verbose responses that increase token costs. This quick-reference card lists all caveman mode triggers, skills, and configuration in one view so you can compress agent output by 65-75 percent.