pytdc
Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and pharmacological prediction.
pyopenms
Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.
pymoo
Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
pymatgen
Materials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
pylabrobot
Laboratory automation toolkit for controlling liquid handlers, plate readers, pumps, heater shakers, incubators, centrifuges, and analytical equipment. Use this skill when automating laboratory workflows, programming liquid handling robots (Hamilton STAR, Opentrons OT-2, Tecan EVO), integrating lab equipment, managing deck layouts and resources (plates, tips, containers), reading plates, or creating reproducible laboratory protocols. Applicable for both simulated protocols and physical hardware control.
benchling-integration
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
astropy
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
arboreto
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
anndata
This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.
alphafold-database
Access AlphaFold's 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
aeon
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
adaptyv
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
youtube-script-master
Unified YouTube script creation for cardiology channels in Hinglish. Uses the COMPLETE research-engine pipeline (channel scraping, comment analysis, narrative monitoring, gap finding, view prediction) combined with RAG + PubMed for evidence. Data-driven topic selection, 15-30 min educational videos with 6-point voice check.
x-post-creator-skill
Create scientifically rigorous, engaging X (Twitter) posts for cardiology thought leadership. Use when generating social media content for a cardiologist targeting patients, caregivers, health optimizers, people with lifestyle diseases (hypertension, diabetes, cholesterol), and sedentary individuals seeking prevention. Produces batches of 10 unique posts using strategic combinations of 300+ cardiology seed ideas, 215+ modifiers, 5 audience archetypes, awareness levels, and proven copywriting frameworks (4A, Magical Multipliers). Features self-improvement through accumulated feedback.
video-delivery-coach
Analyze YOUR video recordings before publishing. Evaluates voice (pace, pitch, volume), facial expressions (emotions, eye contact, smiles), and content (filler words, structure). Helps improve your Hinglish YouTube delivery over time.
twitter-longform-medical
Write data-driven, evidence-first long-form Twitter posts on medicine and cardiology. Use when the user wants to: (1) Create thought leadership content in the style of Eric Topol, Peter Attia, Andrew Huberman, or Rhonda Patrick, (2) Present clinical evidence with charts, data, and Q1 journal citations for educated non-specialist audiences, (3) Write confident, matter-of-fact medical content that is rigorous without being inaccessible, (4) Explain trials, drugs, or medical phenomena using data visualization and systematic evidence review, (5) Build authority through methodological rigor and clear conclusions backed by evidence. NOT for newsletters or Substack. For Twitter long-form posts only.
social-media-trends-research
Programmatic social media and marketing research using free tools: pytrends (Google Trends), yars (Reddit without API keys), and Perplexity MCP (Twitter/TikTok/Web). Use when finding trending topics in a niche, tracking keyword velocity and volume, monitoring Reddit discussions, discovering what's going viral, or researching content opportunities before writing. Zero-cost research stack with built-in rate limiting. Complements content-marketing-social-listening skill with executable code.
perplexity-search
Perform AI-powered web searches with real-time information using Perplexity models via LiteLLM and OpenRouter. This skill should be used when conducting web searches for current information, finding recent scientific literature, getting grounded answers with source citations, or accessing information beyond the model's knowledge cutoff. Provides access to multiple Perplexity models including Sonar Pro, Sonar Pro Search (advanced agentic search), and Sonar Reasoning Pro through a single OpenRouter API key.
parallel-literature-search
Parallel search across PubMed, Perplexity, and your knowledge base. Searches all sources simultaneously and synthesizes findings with citations. Faster evidence gathering for clinical questions.
multi-model-writer
Unified writing system with intelligent model routing. Default: Claude. Options: GLM-4.7 (cheapest), GPT-4o/mini, Gemini, Grok. Includes browser automation for web interfaces. Cost-aware routing based on task complexity.
medical-newsletter-writer
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mcp-management
Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilities, filter MCP tools for specific tasks, execute MCP tools programmatically, access MCP prompts/resources, or implement MCP client functionality. Supports intelligent tool selection, multi-server management, and context-efficient capability discovery.
infographic-generator
Generate world-class medical infographics using carousel-level visual language. Templates include hero stats, multi-section layouts, comparisons, myth-busters, process flows, and patient checklists. Default 1080x1350 for Instagram.
influencer-analyzer
Track and analyze cardiology content creators (Topol, Attia, York Cardiology, Indian channels). Discovers content patterns, topics, engagement, and gap opportunities for your Hinglish content strategy.
docx
Document toolkit (.docx). Create/edit documents, tracked changes, comments, formatting preservation, text extraction, for professional document processing.
scikit-survival
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival data, performing time-to-event analysis, fitting Cox models, Random Survival Forests, Gradient Boosting models, or Survival SVMs, evaluating survival predictions with concordance index or Brier score, handling competing risks, or implementing any survival analysis workflow with the scikit-survival library.
pymc-bayesian-modeling
Bayesian modeling with PyMC. Build hierarchical models, MCMC (NUTS), variational inference, LOO/WAIC comparison, posterior checks, for probabilistic programming and inference.
uniprot-database
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
market-research-reports
Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, deep integration with research-lookup for data gathering, and multi-framework strategic analysis including Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix.
pytorch-lightning
Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.
torch-geometric
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
pysam
Genomic file toolkit. Read/write SAM/BAM/CRAM alignments, VCF/BCF variants, FASTA/FASTQ sequences, extract regions, calculate coverage, for NGS data processing pipelines.
torchdrug
Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.
academic-chapter-writer
Comprehensive academic textbook chapter writing system for medical/scientific content. Use when the user wants to: (1) Write a full textbook chapter (5,000-15,000 words) on any medical/scientific topic, (2) Generate a detailed table of contents with section word counts, (3) Research topics via PubMed MCP and compile 20-30 references, (4) Write section-by-section with proper citations in Vancouver format, (5) Create publishable academic content with Eric Topol-inspired voice and authentic human prose, (6) Get approval at TOC stage before writing begins, (7) Export well-structured chapters for textbook publication.
venue-templates
Access comprehensive LaTeX templates, formatting requirements, and submission guidelines for major scientific publication venues (Nature, Science, PLOS, IEEE, ACM), academic conferences (NeurIPS, ICML, CVPR, CHI), research posters, and grant proposals (NSF, NIH, DOE, DARPA). This skill should be used when preparing manuscripts for journal submission, conference papers, research posters, or grant proposals and need venue-specific formatting requirements and templates.
gwas-database
Query NHGRI-EBI GWAS Catalog for SNP-trait associations. Search variants by rs ID, disease/trait, gene, retrieve p-values and summary statistics, for genetic epidemiology and polygenic risk scores.
uspto-database
Access USPTO APIs for patent/trademark searches, examination history (PEDS), assignments, citations, office actions, TSDR, for IP analysis and prior art searches.
statistical-analysis
Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research.
scikit-learn
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
modal
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
markitdown
Convert files and office documents to Markdown. Supports PDF, DOCX, PPTX, XLSX, images (with OCR), audio (with transcription), HTML, CSV, JSON, XML, ZIP, YouTube URLs, EPubs and more.
matchms
Mass spectrometry analysis. Process mzML/MGF/MSP, spectral similarity (cosine, modified cosine), metadata harmonization, compound ID, for metabolomics and MS data processing.
content-os
Content OS orchestrator - the master skill that produces ALL content types from one seed idea (forward mode) or splits long-form content into short-form pieces (backward mode). Invokes research, writing, quality review, and visual generation skills in a coordinated pipeline. Long-form content goes through full quality gates; short-form gets quick accuracy pass.
content-marketing-social-listening
Comprehensive content marketing toolkit for discovering viral content opportunities, social listening, knowledge gap analysis, and content demand assessment across platforms. Use when researching trending topics in a niche, finding what's going viral, assessing content knowledge gaps, planning content calendars, or identifying high-demand content opportunities. Integrates with perplexity-search for real-time trend data and research-lookup for deep analysis.
carousel-generator
Instagram carousel generator. Creates 1080x1080px branded slides from text/markdown input. Use this skill when you need to generate Instagram carousel slides with Dr. Shailesh Singh's brand colors, typography, and footer. Supports both @heartdocshailesh and @dr.shailesh.singh accounts.
cardiology-youtube-scriptwriter
End-to-end YouTube content creation for cardiology channels. Use when user wants to create YouTube videos about cardiology, heart health, or cardiovascular topics. Triggers on greetings with content intent, requests for video ideas or scripts, help with cardiology YouTube channels, heart health video content requests, or any cardiology content creation conversation. Handles complete workflow from ideation through social listening, topic selection, and full script delivery.
ensemble-content-scorer
Multi-model consensus scoring for content ideas. Scores the same idea with Claude, GPT-4o, Gemini, and Grok in parallel, then aggregates for a balanced verdict. Reduces single-model bias and improves viral predictions.
cardiology-visual-system
Unified visual content system for cardiology thought leadership. Automatically routes requests to the optimal tool—Fal.ai for blog imagery, Gemini for infographics, Mermaid for flowcharts/pathways, Marp for slides, Plotly for data visualization. One skill handles all visual needs within Claude Code.
cardiology-tweet-writer
Generate scientifically accurate, engaging cardiology tweets for thought leadership. Use when creating social media content for a cardiologist targeting patients, health enthusiasts, health optimizers, people with lifestyle diseases, and caregivers. Produces 10 tweets per batch using permutations of cardiology seed ideas and modifiers. Incorporates feedback to improve output quality over time.
cardiology-trial-editorial
Identify landmark cardiology trials and write evidence-based editorials in Eric Topol's authoritative Ground Truths style. Use when the user wants to: (1) Discover and evaluate recent important trials from top cardiology journals (NEJM, JACC, Lancet, EHJ, Circulation), (2) Assess trial importance using systematic scoring, (3) Write 500-word editorials on cardiology/interventional cardiology advances for physician audiences, (4) Create thought leadership content that demonstrates deep domain expertise. Supports both full-text and abstract-only scenarios with PubMed integration for references.
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