Skillz
Skillz from jkitchin/skillz.
Skills in this plugin
34- ▌ Pycse · jkitchin bundleUse when performing regression analysis with confidence intervals, solving ODEs, fitting models to experimental data, or caching expensive scientific computations - provides convenient wrappers around scipy that automatically calculate confidence intervals and prediction bounds for linear, nonlinear, and polynomial regression
- ▌ Eln · jkitchin bundleProfessional scientific documentation in org-mode electronic lab notebooks with date-based organization, comprehensive record-keeping of hypotheses, methods, results, reasoning, and outcomes for reproducible research
- ▌ Tdd · jkitchin bundleTest-Driven Development facilitation using the red-green-refactor cycle. Guides users through writing tests first, implementing minimal code to pass, and refactoring for quality. Use when users want to practice TDD, need help writing tests before code, are developing new features test-first, or want guidance on test structure and implementation. Triggers include 'use TDD,' 'test-driven development,' 'write tests first,' 'red-green-refactor,' or requests to develop functionality with tests.
- ▌ Vasp · jkitchin bundleExpert assistant for VASP (Vienna Ab initio Simulation Package) calculations - input file generation, parameter selection, workflow setup, and best practices for accurate DFT calculations
- ▌ Citation Verifier · jkitchinVerify citations and references in scientific documents to detect hallucinated or invalid sources. Extracts DOIs, URLs, arXiv IDs, PubMed IDs, and ISBNs from Markdown, LaTeX, org-mode, and plain text, then validates them using API lookups and web fetches. Use this skill when: - Reviewing AI-generated content for citation accuracy - Validating references in papers, reports, or documentation - Checking if DOIs/URLs resolve to actual papers - Auditing a document for broken or fake citations
- ▌ Idaes · jkitchin bundleComprehensive guidance for using IDAES (Institute for the Design of Advanced Energy Systems) for process systems engineering. Covers flowsheet modeling, property packages, unit models, optimization, scaling, initialization, and diagnostics. Use when working with chemical process simulations, energy systems modeling, power plant design, material and energy balances, or process optimization. Triggers include 'IDAES', 'flowsheet', 'process model', 'unit operation', 'process optimization', 'property package', 'energy systems', or process engineering tasks.
- ▌ Fairchem · jkitchin bundleExpert guidance for Meta's FAIRChem library - machine learning methods for materials science and quantum chemistry using pretrained UMA models with ASE integration for fast, accurate predictions
- ▌ Pymatgen · jkitchin bundleComprehensive guidance for using pymatgen (Python Materials Genomics) for computational materials science. Covers structure creation and manipulation, file I/O (CIF, POSCAR, XYZ), symmetry analysis, Materials Project API integration, phase diagrams, electronic structure analysis, and DFT input generation. Use when working with crystal structures, materials properties, computational chemistry calculations, or materials databases. Triggers include 'pymatgen', 'crystal structure', 'Materials Project', 'CIF file', 'POSCAR', 'band structure', 'phase diagram', or materials analysis tasks.
- ▌ Planning · jkitchin bundleStructured planning and project breakdown using proven methodologies for goals, projects, and strategic initiatives. Use when users need to create plans, break down complex projects, set milestones, estimate timelines, identify dependencies, or develop action plans. Triggers include 'help me plan,' 'create a roadmap for,' 'break down this project,' 'what are the steps to,' or 'how should I approach.'
- ▌ Pycalphad · jkitchin bundleExpert guidance for pycalphad - computational thermodynamics library implementing the CALPHAD method for calculating phase diagrams, phase equilibria, and thermodynamic properties of multicomponent materials systems using thermodynamic databases (TDB files)
- ▌ Phd Qualifier · jkitchin bundleExpert evaluation of Chemical Engineering PhD qualifying exams - review written reports, presentations, and prepare comprehensive questioning sessions to assess student readiness for doctoral research
- ▌ Brainstorming · jkitchin bundleStructured brainstorming and ideation facilitation using proven creativity techniques. Use when users want to generate ideas, explore solutions, break through creative blocks, or need facilitated ideation sessions. Triggers include requests like 'help me brainstorm,' 'generate ideas for,' 'creative solutions to,' or 'think of alternatives.'
- ▌ Presentations · jkitchinCreate slide presentations in multiple formats: Marp (Markdown, default), Beamer (LaTeX), Jupyter Notebook slides, and PowerPoint (python-pptx). Supports scientific, business, and developer content with math, code, charts, and tables. Converts existing documents into slides or creates from scratch. Auto-compiles to PDF/HTML/PPTX. Use this skill when the user requests: - Creating a presentation or slide deck - Converting a document, paper, or report into slides - Making conference talk, lecture, or meeting slides - Generating PowerPoint, PDF slides, or HTML slideshows - Beamer, Marp, reveal.js, or notebook slideshow creation
- ▌ Python Ase · jkitchin bundleExpert assistance with the Atomic Simulation Environment (ASE) Python library for atomistic simulations, including structure building, calculator setup, optimization, dynamics, and analysis
- ▌ Python Jax · jkitchinExpert guidance for JAX (Just After eXecution) - high-performance numerical computing with automatic differentiation, JIT compilation, vectorization, and GPU/TPU acceleration; includes transformations (grad, jit, vmap, pmap), sharp bits, gotchas, and differences from NumPy
- ▌ Claude Light · jkitchin bundleExpert assistant for conducting remote experiments with Claude-Light - a web-accessible RGB LED and spectral sensor instrument for statistics, regression, optimization, and design of experiments
- ▌ Image Generation · jkitchin bundleAI-powered image generation and editing using Google Gemini, Google Imagen, and OpenAI models. Generate images from text descriptions, edit existing images, create logos/stickers, apply style transfers, and produce product mockups. Use this skill when the user requests: - Image generation from text descriptions - Image editing or modifications - Logos, stickers, or graphic design assets - Product mockups or visualizations - Style transfers or artistic effects - Iterative image refinement Available models: - Google Gemini: gemini-2.5-flash-image (Nano Banana), gemini-3-pro-image-preview (Nano Banana Pro) - Google Imagen: imagen-4.0-generate-001, imagen-4.0-ultra-generate-001, imagen-4.0-fast-generate-001 - OpenAI: gpt-image-1.5 (recommended), gpt-image-1, dall-e-3, dall-e-2 Inspired by: https://github.com/EveryInc/every-marketplace/tree/main/plugins/compounding-engineering/skills/gemini-imagegen
- ▌ Code Reviewer · jkitchin bundleComprehensive code review and analysis for software quality assurance. Use when Claude needs to review code in any format including (1) Individual files (Python, R, JavaScript, etc.), (2) Directory structures and project organization, (3) Scripts and automation code, (4) Jupyter notebooks and data analysis workflows, (5) Documentation assessment and improvement suggestions, (6) Bug detection and logic verification, (7) Testing coverage and strategy evaluation, (8) Code consistency and maintainability analysis. Provides actionable improvement recommendations across all aspects of software development.
- ▌ Troubleshooting · jkitchin bundleSystematic debugging and problem diagnosis using structured troubleshooting methodologies applicable to any domain - technical issues, process failures, system problems, or general obstacles. Use when users report errors, describe malfunctions, encounter unexpected behavior, or need help diagnosing root causes. Triggers include 'debug this,' 'troubleshoot,' 'why isn't this working,' 'getting an error,' 'something's wrong with,' 'how do I fix,' or any problem description.
- ▌ Literature Review · jkitchin bundleConduct systematic scientific literature reviews by integrating multi-source searches, iterative analysis, and synthesis into well-structured reports with proper citations. Use this skill when you need to: synthesize knowledge across multiple research domains, identify research gaps, track the evolution of methodologies, evaluate evidence quality, or write comprehensive literature reviews for academic papers, grant proposals, or research projects. Key capabilities: multi-database search strategies, iterative query refinement, content analysis and summarization, thematic synthesis, citation management, quality assessment, bias detection, and structured report generation with multiple output formats.
- ▌ Version Control · jkitchin bundleExpert guidance for Git version control, trunk-based development workflows, and GitHub best practices. Emphasizes Conventional Commits for clean history, short-lived feature branches, frequent integration, and professional collaboration patterns. Use when users need help with git commands, branching strategies, commit messages, PRs, merge conflicts, or git troubleshooting. Triggers include 'git,' 'commit,' 'branch,' 'merge,' 'rebase,' 'PR,' 'pull request,' or version control questions.
- ▌ Python Plotting · jkitchinComprehensive plotting and visualization in Python - matplotlib (static publication-quality plots), seaborn (statistical visualization), and plotly (interactive plots); includes plot types, customization, best practices, and library selection guidance
- ▌ Materials Databases · jkitchin bundleExpert assistant for accessing materials databases (AFLOW and Materials Project) - query crystal structures, materials properties, thermodynamic data, and computational results from comprehensive databases
- ▌ Scientific Reviewer · jkitchin bundleComprehensive scientific document review and analysis. Use when Claude needs to review scientific papers, reports, preprints, or other research documents for: (1) Identifying and evaluating claims and supporting evidence, (2) Assessing logical argumentation and experimental design, (3) Reviewing citation adequacy and suggesting additional references, (4) Determining document type and research contribution, (5) Checking technical accuracy and methodology, (6) Providing constructive feedback on presentation and clarity. Also handles language, grammar, and formatting review separately.
- ▌ Scientific Workflows · jkitchin bundleExpert assistant for choosing and implementing scientific workflow tools - from simple joblib caching to complex orchestration with Prefect, Parsl, FireWorks, and quacc. Recommends the simplest solution that meets requirements.
- ▌ Scientific Writing · jkitchin bundleComprehensive scientific writing guidance for research papers, grants, and technical documentation. Covers paper structure (IMRAD), methods writing, results presentation, figure/table design, citation formatting, abstract writing, and revision responses. Use when users are writing scientific papers, formatting manuscripts, responding to reviewers, writing grant proposals, or need help with any aspect of scientific communication. Triggers include 'write a paper,' 'scientific writing,' 'format my manuscript,' 'methods section,' 'respond to reviewers,' or any research writing task.
- ▌ Materials Properties · jkitchin bundleExpert assistant for calculating materials properties from first-principles using ASE - structure relaxation, surface energies, adsorption, reaction barriers, phonons, elastic constants, and thermodynamic modeling with proper scientific methodology
- ▌ Design Of Experiments · jkitchin bundleExpert guidance for Design of Experiments (DOE) in Python - interactive goal-driven design selection, classical DOE (factorial, response surface, screening), Bayesian optimization with Gaussian processes, model-driven optimal designs, active learning, and sequential experimentation; includes pyDOE3, pycse, BoTorch, Ax, scikit-optimize, statsmodels
- ▌ Opentrons Thermocycler · jkitchinOpentrons Thermocycler Module - automated PCR thermal cycling with independent block (4-99°C) and lid (37-110°C) temperature control, profile execution, and auto-sealing lid support (GEN2) for high-throughput molecular biology workflows
- ▌ Python Best Practices · jkitchin bundleExpert guidance for writing professional Python code following industry best practices including PEP 8 compliance, testing, type hints, error handling, and modern tooling. Use this skill when writing new Python code, refactoring existing code, setting up Python projects, implementing tests, or ensuring code quality and maintainability. Emphasizes: PEP 8, modularity, DRY principle, TDD, virtual environments (uv), and modern tooling (Ruff, Black, Mypy).
- ▌ Opentrons Heater Shaker · jkitchinOpentrons Heater-Shaker Module - temperature control (37-95°C) with orbital mixing (200-3000 rpm) for cell culture, enzymatic reactions, and sample preparation requiring simultaneous heating and agitation
- ▌ Scientific Data Extraction · jkitchin bundleExtract structured data from scientific literature across multiple formats (PDF, HTML, images, plain text). Auto-detects scientific domain to recommend specialized tools for chemistry/materials when appropriate. Use this skill when: extracting numerical data from papers, digitizing graphs/plots, parsing tables from PDFs, extracting chemical properties or reactions, or converting unstructured scientific text to structured formats. Key capabilities: format detection and routing, domain-specific extraction (chemistry/materials), multi-method validation, table extraction, graph digitization, LLM-enhanced extraction with verification, confidence scoring.
- ▌ Opentrons Absorbance Reader · jkitchinOpentrons Absorbance Plate Reader Module for Flex - on-deck microplate spectrophotometry with single/multi-wavelength reading (380-740nm in 10nm increments), automated lid control, and CSV data export for ELISA, cell growth, and colorimetric assays
- ▌ Python Multiobjective Optimization · jkitchinExpert guidance for multiobjective optimization in Python - Pareto optimality, evolutionary algorithms (NSGA-II, NSGA-III, MOEA/D), scalarization methods, Pareto front analysis, and implementation with pymoo, platypus, and DEAP