mkurman
- 482 skills
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- 10 hours ago last updated
- ▌ Directory Submissions · mkurman bundleWhen the user wants to submit their product to startup, SaaS, AI, agent, MCP, no-code, or review directories for backlinks, domain rating, and discovery. Also use when the user mentions "directory submissions," "submit to directories," "backlinks from directories," "list my product," "submit to Product Hunt," "BetaList," "TAAFT," "Futurepedia," "G2 listing," "Capterra listing," "AlternativeTo," "SaaSHub," "AI directories," "MCP registry," "agent directory," "dofollow backlinks," "launch directories," or "directory tracker." Use this whenever someone is planning the directory layer of a product launch or an ongoing backlink campaign. For the broader launch moment, see launch-strategy. For programmatic SEO pages that should live behind these backlinks, see programmatic-seo. For AI citation optimization, see ai-seo.
- ▌ Competitive Analysis · mkurmanWhen the user needs to evaluate competitors, understand the competitive landscape, or position their product against alternatives.
- ▌ Protein Sequence Similarity Search · mkurman bundleSearches for homologous protein sequences using MMseqs2 (fast, default) or BLAST (comprehensive, fallback). Trigger this whenever the user provides a protein sequence or FASTA file and asks to find homologues, sequence matches, or wants to infer protein function based on sequence similarity, but not when the user wants to infer protein function based on structural similarity.
- ▌ Earned Media Outreach · mkurmanWhen the user wants to get press coverage, appear on podcasts, or build relationships with journalists and content creators. Also use when the user mentions "podcast guesting", "press outreach", "PR", "media exposure", "get on podcasts", or "journalist outreach".
- ▌ Alphagenome Single Variant Analysis · mkurman bundleAnalyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical significance, disease associations, functional effects, gene expression changes, splicing disruption, or regulatory effects in promoters and enhancers. Also use for resolving biological terms to tissue/cell-type ontologies (UBERON/CL) or analyzing variants in chr:pos:ref>alt format.
- ▌ Alphafold Database Fetch And Analyze · mkurman bundleRetrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.
- ▌ User Research Synthesis · mkurmanWhen the user has raw customer interview transcripts, survey responses, support tickets, or other qualitative data and needs to extract actionable insights.
- ▌ Data Diff · mkurmanCompare two dataset versions and produce a structured diff — what was added, removed, changed, with row counts and field-level change summaries.
- ▌ Pr Triage · mkurmanUse when the user wants a pull request review queue summary, morning PR check, stale PR scan, or a routine-ready GitHub triage summary delivered to chat.
- ▌ Bias Audit · mkurmanAudit dataset bias across protected attributes — demographic parity, equalized odds, representation gaps, and intersectional bias. Reports actionable gaps with per-group metrics.
- ▌ Daily Brief · mkurmanUse when the user wants a morning brief, start-of-day summary, routine-ready daily digest, or a concise operational overview combining calendar, tasks, PRs, and issues.
- ▌ Hf Datasets · mkurmanLoad, stream, process, and publish datasets with the HuggingFace datasets library. Covers Apache Arrow-backed streaming for large datasets, map/filter operations, train/val/test splitting, interleaving, concatenation, and pushing to the Hub.
- ▌ Inbox Triage · mkurmanUse when the user wants an inbox cleanup summary, morning email triage, scheduled inbox sweep, or a concise action-oriented Gmail digest delivered to chat.
- ▌ Data Card Writer · mkurmanGenerate structured datasheets for datasets (Gebru et al. "Datasheets for Datasets" format) — purpose, composition, collection process, preprocessing, limitations, and licensing.
- ▌ Dataset Cleaning · mkurmanClean, normalize, and prepare raw datasets for analysis or ML. Covers missing value handling, deduplication, outlier treatment, type normalization, categorical encoding, and transformation logging.
- ▌ Btw · mkurmanAsk a quick side question about your current work without derailing the main task. Answers from existing conversation context only — no tool calls, no file reads, single concise response. Use when you need a fast answer from what is already in this session.
- ▌ Dataset Splitting · mkurmanCreate reproducible train/validation/test splits with stratification, leakage prevention, and distribution validation. Covers random, stratified, grouped, and time-series split strategies.
- ▌ Lint · mkurmanLint and format code. Auto-detects ESLint, Biome, Prettier, or language-native formatters and runs them with auto-fix. Reports remaining issues with actionable suggestions.
- ▌ Test · mkurmanGenerate or run tests. Auto-detects test framework, generates comprehensive tests for source files, or runs existing test suites with failure analysis.
- ▌ Lsp Code Analysis · mkurman bundleSemantic code analysis via LSP. Navigate code (definitions, references, implementations), search symbols, preview refactorings, and get file outlines. Use for exploring unfamiliar codebases or performing safe refactoring.
- ▌ Dataset Versioning · mkurmanVersion datasets with checksums, manifests, and semantic versioning. Covers DVC integration, provenance tracking, release tagging, and reproducible dataset lifecycles.
- ▌ Embedding Analysis · mkurmanCompute and analyze embeddings for dataset quality, distribution comparison, semantic deduplication, diversity measurement, and similarity-based filtering. Covers sentence-transformers, embedding space diagnostics, and 2025-2026 literature techniques (NeMo Curator semantic dedup, embedding similarity metrics for data selection, DataRater-style quality scoring).
- ▌ Review · mkurmanReview code changes for security, performance, bugs, and quality. Reviews staged changes, unstaged changes, specific commits, or PR-ready diffs.
- ▌ Label Quality Audit · mkurmanAudit label quality using confident learning (Northcutt et al.), cross-validation noise detection, and per-class error analysis. Identifies mislabeled examples for review.
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- ▌ LLM Assisted Curation · mkurmanUse locally-hosted LLMs (vLLM/SGLang) for dataset filtering, quality scoring, rewriting, labeling, and synthetic data generation. Covers LLM-as-judge scoring, structured output filtering, batch inference pipelines, and 2025-2026 techniques (DataRater, perplexity filtering, curriculum scoring, LLM-based dedup).
- ▌ Gdm Science Bundle · mkurman bundleVendor of the google-deepmind/science-skills bundle (37 skills for scientific research). Use when a user asks about any of: AlphaGenome single-variant effect analysis (RNA-seq / DNase / ChIP / TF effects, splicing disruption, UBERON/CL ontology resolution for non-coding variants), AlphaFold DB fetch and analyze, ChEMBL bioactivity queries, ClinicalTrials.gov lookups, ClinVar variant interpretation, dbSNP, EMBL-EBI Ontology Lookup Service (OLS4), ENCODE cCREs, Ensembl REST, Foldseek structural search, gnomAD, GTEx, Human Protein Atlas, InterPro, JASPAR transcription-factor profiles, literature search (arXiv / bioRxiv / EuropePMC / OpenAlex), NCBI sequence fetch (EFetch), openFDA, OpenTargets, PDB, protein sequence MSA / similarity search, PubChem, PubMed, PyMOL structural visualization, QuickGO, Reactome, STRING, UCSC conservation & TFBS, UniBind, UniProt, or any workflow combining them. Always read the per-skill SKILL.md under skills/<name>/ and invoke Python only through `uv run`.
- ▌ Dgl · mkurmanDeep Graph Library (DGL) — graph neural network framework. GCN, GAT, GraphSAGE, RGCN, and custom message-passing. Heterogeneous graphs, temporal graphs, and large-scale training with mini-batch sampling.
- ▌ PDF · mkurman bundleUse this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.
- ▌ Sdv · mkurmanSynthetic Data Vault (SDV) — generate synthetic tabular data. Single-table, multi-table, and sequential data synthesis. CTGAN, TVAE, CopulaGAN, GaussianCopula. Privacy metrics and evaluation.
- ▌ Trl · mkurmanTransformer Reinforcement Learning library (TRL). Supervised fine-tuning (SFT), reward modeling, PPO, DPO, KTO, GRPO for RLHF. Process reward models and language model alignment.
- ▌ Ccxt · mkurmanUnified cryptocurrency exchange trading API. 100+ exchange clients (Binance, Coinbase, Kraken, Bybit, OKX). Market data, order management, websocket streaming, and arbitrage workflows.
- ▌ Clip · mkurmanOpenAI CLIP — contrastive language-image pre-training. Zero-shot image classification, image-text similarity, concept search, and cross-modal retrieval. Embed images and text into shared space.
- ▌ DOCX · mkurman bundleUse this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
- ▌ Fhir · mkurmanFHIR (Fast Healthcare Interoperability Resources) standard. Tools for reading, writing, and querying healthcare data via FHIR APIs: patients, observations, conditions, medications, procedures. Interop with EHR systems.
- ▌ Peft · mkurmanParameter-Efficient Fine-Tuning (PEFT) library. LoRA, QLoRA, AdaLoRA, IA3, Prefix Tuning, P-Tuning, Prompt Tuning. Fine-tune large models with minimal memory overhead. Hugging Face ecosystem integration.
- ▌ PPTX · mkurman bundleUse this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill.
- ▌ Vllm · mkurmanFast LLM inference engine. PagedAttention, continuous batching, tensor parallelism, speculative decoding, and prefix caching. OpenAI-compatible API server. Supports Llama, Mistral, Qwen, DeepSeek, and hundreds of models.
- ▌ Darts · mkurmanDarts — time series forecasting library by Unit8. Unified API across ARIMA, Prophet, CatBoost, N-BEATS, TFT, TCN, Transformer, and RNN models. Backtesting, probabilistic forecasting, and covariate support.
- ▌ Dowhy · mkurmanDoWhy (Microsoft) — causal inference library. Causal graph modeling, identification (back-door, front-door, IV), estimation (matching, IPW, double-ML), and refutation/robustness checks for causal claims.
- ▌ Feast · mkurmanFeast — open-source feature store. Online and offline serving, point-in-time joins, feature validation, and streaming ingestion. Standardizes feature management across training and production.
- ▌ Hydra · mkurmanConfiguration framework for complex applications (Hydra). Dynamic hierarchical configuration by composition and override via CLI, YAML, and structured configs. Use for ML experiment management, multi-environment deployment, hyperparameter sweeps, and reproducible research workflows. Integrates with PyTorch Lightning, Weights & Biases, MLflow, and Optuna.
- ▌ Mimic · mkurmanMIMIC (Medical Information Mart for Intensive Care) database toolkit. Curated ICU data: vitals, labs, medications, notes, diagnoses. Tools for querying MIMIC-III/IV, building ML features, and reproducing benchmarks.
- ▌ Modal · mkurman bundleCloud computing platform for running Python on GPUs and serverless infrastructure. Use when deploying AI/ML models, running GPU-accelerated workloads, serving web endpoints, scheduling batch jobs, or scaling Python code to the cloud. Use this skill whenever the user mentions Modal, serverless GPU compute, deploying ML models to the cloud, serving inference endpoints, running batch processing in the cloud, or needs to scale Python workloads beyond their local machine. Also use when the user wants to run code on H100s, A100s, or other cloud GPUs, or needs to create a web API for a model.
- ▌ Monai · mkurmanMedical Open Network for AI (MONAI). Framework for deep learning in medical imaging: segmentation, classification, detection, registration. Supports DICOM, NIfTI, PNG. Built on PyTorch with GPU acceleration.
- ▌ Pymoo · mkurman bundleMulti-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.
- ▌ Rowan · mkurmanRowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
- ▌ Simpy · mkurman bundleProcess-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.
- ▌ Wandb · mkurmanWeights & Biases — ML experiment tracking and visualization. Log metrics, hyperparameters, model checkpoints, and artifacts. Collaborative dashboards, sweep hyperparameter search, and model registry.
- ▌ Zenml · mkurmanZenML — ML pipeline orchestration. Connect ML tools (MLflow, W&B, Airflow, Kubeflow) into portable pipelines. Caching, versioning, and cloud-agnostic stack management for production ML workflows.
- ▌ Github Triage · mkurman bundleTriage GitHub issues through a label-based state machine. Use when user wants to create an issue, triage issues, review incoming bugs or feature requests, prepare issues for an AFK agent, or manage issue workflow.
- ▌ Write A Skill · mkurmanCreate new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, or build a new skill.
- ▌ Captum · mkurmanCaptum (PyTorch) — model interpretability and feature attribution. Integrated Gradients, DeepLIFT, SmoothGrad, Occlusion, SHAP approximation, and Layer-wise Relevance Propagation. For vision and text models.
- ▌ Crewai · mkurmanCrewAI — multi-agent AI framework. Role-based agents with defined goals, tools, and memory. Hierarchical and sequential task execution. Human input delegation and process orchestration.
- ▌ Depmap · mkurman bundleQuery the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores (CRISPR Chronos), drug sensitivity data, and gene effect profiles. Use for identifying cancer-specific vulnerabilities, synthetic lethal interactions, and validating oncology drug targets.
- ▌ Econml · mkurmanEconML (Microsoft) — heterogeneous treatment effect estimation. Double ML, Causal Forest, Deep IV, and metalearners (S-Learner, T-Learner, X-Learner). Orthogonal learning for causal effects from observational data.
- ▌ Medcat · mkurmanMedical Concept Annotation Toolkit. Trainable NLP for extracting clinical concepts from unstructured text. Supports ICD-10, SNOMED CT, RxNorm, UMLS. Active learning for custom medical ontologies.
- ▌ Milvus · mkurmanMilvus — cloud-native vector database for billion-scale similarity search. GPU-accelerated indexing, hybrid search, multi-vector, streaming, and time travel. Distributed deployment with Kubernetes.
- ▌ Mlflow · mkurmanMLflow — open-source MLOps platform. Experiment tracking, model registry, packaging, deployment, and evaluation. Multi-cloud ML workflows with reproducible runs and artifact logging.
- ▌ Nixtla · mkurmanNixtla ecosystem — statsforecast (statistical), neuralforecast (deep learning), hierarchicalforecast, and MLForecast. Production time series forecasting with AutoARIMA, ETS, Theta, Transformers, and ensemble blending.
- ▌ Nnunet · mkurmanNo New U-Net — self-configuring framework for medical image segmentation. Automatically adapts to any dataset. Top performer on biomedical segmentation benchmarks (BraTS, KiTS, etc.).
- ▌ Ollama · mkurmanLocal LLM runner. One-command setup for Llama, Mistral, Gemma, Qwen, DeepSeek, Phi, and 100+ models. OpenAI-compatible API, model management, GPU acceleration, and custom Modelfile creation.
- ▌ Optuna · mkurman bundleHyperparameter optimization framework (Optuna). Define-by-run API with automatic search space construction, state-of-the-art samplers (TPE, CMA-ES, NSGA-II, GPSampler), efficient pruning (Median, Hyperband, ASHA), multi-objective optimization, constrained optimization, distributed parallel execution, and visualization dashboard. Integrates with PyTorch, PyTorch Lightning, TensorFlow, Keras, XGBoost, LightGBM, CatBoost, MLflow, W&B, and scikit-learn.
- ▌ Polars · mkurman bundleFast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.
- ▌ Qdrant · mkurmanQdrant — vector similarity search engine. Payload filtering, quantized indexing, multi-tenant, and horizontal scaling. REST and gRPC API. Docker-native deployment for production RAG and recommendation.
- ▌ Scvelo · mkurman bundleRNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.
- ▌ Sglang · mkurmanStructured Generation Language for LLM serving. RadixAttention prefix caching, constrained decoding (JSON, grammar), OpenAI-compatible API, and multi-turn optimization. Fast inference with structured output guarantees.
- ▌ Create Skill · mkurman bundleExpert guidance for creating, writing, building, and refining GSD skills. Use when working with SKILL.md files, authoring new skills, improving existing skills, or understanding skill structure and best practices.
- ▌ Adaptyv · mkurman bundleHow to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
- ▌ Autogen · mkurmanAutoGen (Microsoft) — multi-agent conversation framework. Agent-to-agent chat, code generation & execution, tool use, group chat, and human-in-the-loop. Build collaborative AI systems with specialized agents.
- ▌ Axolotl · mkurmanStreamlined fine-tuning framework for LLMs. Supports full fine-tune, LoRA, QLoRA, FSDP, DeepSpeed, and multi-GPU. YAML config driven. Works with Llama, Mistral, Qwen, DeepSeek, and hundreds of HF models.
- ▌ Bentoml · mkurmanBentoML — model serving and deployment. Build prediction services from any ML framework with OpenAPI/Swagger. Containerize, deploy to Kubernetes, AWS, GCP, Azure. Adaptive batching and GPU support.
- ▌ Cleanrl · mkurmanSingle-file deep reinforcement learning implementations (CleanRL). High-quality standalone implementations of PPO, DQN, C51, SAC, DDPG, TD3 with research-friendly features. Each algorithm is a self-contained file with ~300-500 lines. Includes Atari, MuJoCo, Procgen, PettingZoo multi-agent, and JAX variants. Use for RL algorithm reference, rapid prototyping, and understanding implementation details.
- ▌ Fredapi · mkurmanFederal Reserve Economic Data (FRED) API client. 800,000+ US and international economic time series: GDP, inflation, unemployment, interest rates, industrial production. Direct data access for macro research.
- ▌ Lancedb · mkurmanLanceDB — serverless vector database for AI. Columnar storage on Lance format, zero-copy access, multimodal search (text + images + audio), and direct DataFrame integration. No separate server.
- ▌ Molfeat · mkurman bundleMolecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
- ▌ Nanogpt · mkurmanMinimal GPT pretraining and fine-tuning (nanoGPT). The simplest, fastest repository for training medium-sized GPTs with ~300-line model.py and ~300-line train.py. Reproduces GPT-2 (124M) on OpenWebText. Supports DDP multi-GPU/multi-node, character-level training, weight loading from HuggingFace GPT-2 checkpoints, and simple finetuning. Note: superseded by nanochat for new projects; this repo remains valuable as a reference implementation and learning tool.
- ▌ Nibabel · mkurmanRead and write neuroimaging file formats: NIfTI, GIFTI, CIFTI, MGH, Minc, Analyze, SPM. Core I/O for fMRI, diffusion MRI, structural MRI pipelines. Use when handling brain imaging data.
- ▌ Openmed · mkurman bundleProduction-ready medical NLP toolkit (maziyarpanahi/openmed). Entity extraction, assertion detection, PII de-identification, batch processing, REST API, and multilingual support. Covers installation, all model families, configuration, and deployment.
- ▌ Prophet · mkurmanMeta Prophet — forecasting at scale. Additive model with yearly/weekly/daily seasonality, holiday effects, changepoints, and trend decomposition. Handles missing data and outliers automatically.
- ▌ Unsloth · mkurmanFast QLoRA/QLoRA fine-tuning with 2x faster training and 50% less memory. Supports Llama, Mistral, Gemma, Qwen, DeepSeek, Phi, Yi, Falcon. Flash Attention, 4-bit quantization. No quality loss.
- ▌ Whisper · mkurmanOpenAI Whisper — general-purpose speech recognition. Multilingual transcription, translation to English, and speaker-agnostic ASR. Models from tiny to large. Robust to noise, accents, and technical vocabulary.
- ▌ Synthlabs Setup · mkurmanUse when you need to locate, start, and verify a local SynthLabs backend before API-dependent work.
- ▌ Triton Kernel Programming · mkurman bundleHands-on implementation template and API reference for writing, tuning, debugging, and benchmarking Triton GPU kernels. Covers the full triton.language API surface, autotuning patterns, profiling workflows, and production integration.
- ▌ Accessibility · mkurman bundleAudit and improve web accessibility following WCAG 2.1 guidelines. Use when asked to "improve accessibility", "a11y audit", "WCAG compliance", "screen reader support", "keyboard navigation", or "make accessible".
- ▌ Agent Browser · mkurman bundleBrowser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
- ▌ Arboreto · mkurman bundleInfer 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.
- ▌ Chromadb · mkurmanChroma — AI-native embedding database. In-process, lightweight vector store with automatic embedding, metadata filtering, and full-text search. Simplest path from prototype to production RAG.
- ▌ Deepchem · mkurman bundleMolecular ML with diverse featurizers and pre-built datasets. Use for property prediction (ADMET, toxicity) with traditional ML or GNNs when you want extensive featurization options and MoleculeNet benchmarks. Best for quick experiments with pre-trained models, diverse molecular representations. For graph-first PyTorch workflows use torchdrug; for benchmark datasets use pytdc.
- ▌ Diffdock · mkurman bundleDiffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.
- ▌ Fluidsim · mkurman bundleFramework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
- ▌ Pydeseq2 · mkurman bundleDifferential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.
- ▌ Pyhealth · mkurman bundleComprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data. This skill should be used when working with electronic health records (EHR), clinical prediction tasks (mortality, readmission, drug recommendation), medical coding systems (ICD, NDC, ATC), physiological signals (EEG, ECG), healthcare datasets (MIMIC-III/IV, eICU, OMOP), or implementing deep learning models for healthcare applications (RETAIN, SafeDrug, Transformer, GNN).
- ▌ Pymatgen · mkurman bundleMaterials science toolkit. Crystal structures (CIF, POSCAR), phase diagrams, band structure, DOS, Materials Project integration, format conversion, for computational materials science.
- ▌ Pyopenms · mkurman bundleComplete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing. For simple spectral comparison and metabolite ID use matchms.
- ▌ Pyzotero · mkurman bundleInteract with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.
- ▌ Tensorrt · mkurmanNVIDIA TensorRT — deep learning inference optimizer. FP16/INT8/INT4 quantization, kernel auto-tuning, layer fusion, and dynamic shapes. Max throughput on NVIDIA GPUs for production inference.
- ▌ Weaviate · mkurmanWeaviate — open-source vector database with built-in ML. Hybrid search (vector + keyword), generative search, graph connections, multi-modal (text + image), and automatic schema inference.
- ▌ Yfinance · mkurmanYahoo Finance market data downloader. Stock prices, options chains, fundamentals, dividends, splits, earnings, institutional holders, and financial statements. Quick data ingestion for quant research and backtesting.
- ▌ Best Practices · mkurmanApply modern web development best practices for security, compatibility, and code quality. Use when asked to "apply best practices", "security audit", "modernize code", "code quality review", or "check for vulnerabilities".