Ric Fulop
Community@ricfulop · Lexington, MA USA
Ric Fulop's registry delivers 35 open-source skills for scientific computing, academic writing, statistical modeling, and publication-grade research visualization.
Agent Skills by Ric Fulop
Showing 33 vetted skills indexed across 1 GitHub repositories.
ricfulopmit-presentation
Generate academic PowerPoint decks from the official MIT Arial template using python-pptx.
ricfuloppymc
Build, fit, and validate Bayesian models with PyMC using MCMC and variational inference.
ricfulopsympy
Perform exact symbolic mathematics in Python including algebra, calculus, equation solving, and code generation.
ricfulopverify-before-claiming
Validates numbers, statuses, and citations against generating code or primary records before publication.
ricfulopscientific-schematics
Generate scientific diagrams from natural language prompts using Nano Banana 2 with Gemini quality review.
ricfuloppyzotero
Manage Zotero libraries programmatically via the Zotero Web API v3 using Python.
ricfulopseaborn
Create statistical visualizations from pandas DataFrames using seaborn plotting functions.
ricfulopfluidsim
Runs pseudospectral CFD simulations of Navier-Stokes, shallow water, and stratified flows in Python.
ricfuloppymatgen
Analyze crystal structures, phase diagrams, and electronic properties with pymatgen and Materials Project.
ricfulopcitation-management
Search academic databases, extract metadata, and generate validated BibTeX citations.
ricfulopscientific-critical-thinking
Evaluate scientific claims, study designs, biases, and evidence quality using GRADE and Cochrane frameworks.
ricfulopresearch-grants
Write competitive research proposals for NSF, NIH, DOE, DARPA, and Taiwan NSTC funding programs.
ricfulopliterature-corpus
Directs literature corpus building to the domain-corpus-bootstrap workflow before domain analysis.
ricfulopmanuscript-prose-style
Edits LaTeX research manuscripts for American English, noun-phrase headings, and machine-generation tells.
ricfulopstatistical-analysis
Guides statistical test selection, assumption checking, power analysis, and APA-formatted reporting in Python.
ricfulopscientific-writing
Write scientific manuscripts in IMRAD structure with citations, figures, and reporting guidelines.
ricfuloppaper-lookup
Search ten academic paper databases via REST APIs for papers, citations, and full text.
ricfulopdual-source-honesty
Keeps fetch-time catalogs distinct from corrected bibliographies and labels numeric values by provenance status.
ricfulopliterature-review
Conduct systematic literature reviews across academic databases with verified citations and PDF output.
ricfulopscholar-evaluation
Evaluate scholarly work across eight quality dimensions using the ScholarEval framework with structured scoring.
ricfulopprereg-freeze
Freezes confirmatory research protocols as hash-bound, append-only records before runs.
ricfulopmatplotlib
Create static, animated, and interactive plots in Python with matplotlib.
ricfulopvenue-templates
Provides LaTeX templates, formatting requirements, and writing style guides for academic journals, conferences, posters, and grant proposals.
ricfulopscientific-visualization
Create and audit publication-ready scientific figures with Matplotlib, Seaborn, and Plotly.
Frequently Asked Questions About Ric Fulop
FAQPage SchemaWhat tasks can I accomplish with ricfulop's skill registry?▼
You can run Bayesian inference with PyMC, symbolic math with SymPy, CFD simulations with Fluidsim, materials analysis with Pymatgen, multi-objective optimization with pymoo, systematic literature reviews, grant writing for NSF/NIH/DOE/DARPA, and publication-grade figure creation for Nature, Science, and APS venues.
Who should use these scientific research skills?▼
Academic researchers, computational scientists, graduate students, and R&D engineers benefit most. The skills target users writing manuscripts, preparing grant proposals, running statistical or machine-learning analyses, managing Zotero bibliographies, and producing peer reviews or preregistered confirmatory studies.
What are the installation and runtime requirements?▼
Most skills require Python 3.9-3.11+ with libraries installed via pip or uv, such as scikit-learn 1.7+, SymPy 1.14+, or pyzotero 1.13+. Some features need API keys (Zotero, OpenRouter) or a Chrome/Chromium install for Plotly static export via Kaleido.
Are these skills free and open source?▼
Yes. All skills carry permissive open-source licenses including MIT, Apache-2.0, BSD-3-Clause, and CeCILL. There is no licensing cost; only optional third-party services like OpenRouter or Zotero Web API access may require user-provided credentials.
How do the skills support research integrity and reproducibility?▼
Dedicated skills enforce verification before citing numbers, separate fetch-time catalogs from corrected bibliographies, hash-bind preregistrations before confirmatory runs, and apply GRADE/Cochrane evidence grading plus ScholarEval scoring for structured manuscript assessment.