
Claude Skills by jkitchin
github.com/jkitchinExpert evaluation of Chemical Engineering PhD qualifying exams - review written reports, presentations, and prepare comprehensive questioning sessions to assess student readiness for doctoral research
Verify 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
Comprehensive 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 ...
Structured 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.'
AI-powered audio generation using ElevenLabs API - text-to-speech with lifelike voices, sound effects generation, and music creation from text descriptions. Generate natural-sounding speech in 32 languages, create custom sound effects for games and videos, and compose royalty-free music tracks. Use this skill when the user requests: - Voice generation or text-to-speech conversion - Audio narration for content (videos, audiobooks, podcasts) - Sound effects for games, videos, or applications -...
AI-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 Av...
Comprehensive 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 maintai...
Test-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.
Expert 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.
A skill on generative optimization for using Gaussian Mixture Models and Conditional Flow matching models for optimization tasks.
Opentrons Absorbance Plate Reader Module for Flex - on-deck microplate spectrophotometry with single/multi-wavelength reading (450, 562, 600, 650nm), automated lid control, and CSV data export for ELISA, cell growth, and colorimetric assays
Opentrons Flex Gripper - automated labware movement between deck locations, modules, waste chute, and off-deck storage with precise positioning and offset control for hands-free plate transfers
Opentrons 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
Opentrons Magnetic Block for Flex - unpowered magnetic bead separation using gripper-based labware movement with high-strength neodymium magnets for DNA/RNA purification, immunoprecipitation, and bead-based workflows
Opentrons Temperature Module - precise heating and cooling (4-95°C) for sample storage, enzyme reactions, and temperature-sensitive protocols with aluminum block adapters for plates, tubes, and PCR strips
Opentrons 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
Expert guidance for Opentrons Python API v2 - automated liquid handling, protocol development, labware management, and hardware module integration for OT-2 and Flex robots
Structured 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.'
Expert 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
Expert guidance for writing professional Emacs Lisp code following the community-driven Emacs Lisp Style Guide by Bozhidar Batsov. Covers layout, naming conventions, syntax preferences, macros, documentation, and best practices. Use this skill when writing Emacs configuration, creating Emacs packages, writing interactive commands, developing major/minor modes, or refactoring Emacs Lisp code. Emphasizes: lexical binding, proper naming, documentation standards, autoloading, and community conv...
Comprehensive 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', 'prope...
Expert 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
Expert 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)
Comprehensive 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 Pro...
Expert assistance with the Atomic Simulation Environment (ASE) Python library for atomistic simulations, including structure building, calculator setup, optimization, dynamics, and analysis
Expert 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).
Expert 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
Expert 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
Expert guidance for mathematical optimization in Python - systematic problem classification, library selection (scipy, pyomo, cvxpy, GEKKO), solver configuration, and implementation patterns for LP, QP, NLP, MIP, convex, and global optimization problems
Comprehensive 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
Expert guidance for regression analysis, statistical modeling, and outlier detection in Python using statsmodels, scikit-learn, scipy, and PyOD - includes model diagnostics, assumption checking, robust methods, and comprehensive outlier detection strategies
Use 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
Professional 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
Conduct 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 str...
Expert assistant for accessing materials databases (AFLOW and Materials Project) - query crystal structures, materials properties, thermodynamic data, and computational results from comprehensive databases
Extract 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-specif...
Expert 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.
Expert 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, GPyOpt, scikit-optimize, statsmodels
Systematic 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.