By sciris
Leverage Claude skills to use Sciris for scientific Python workflows: manipulate arrays with smoothing/regression, plot with Matplotlib utils, parallelize functions with CPU/memory limits, handle dates/timing/file I/O, print progress, and access advanced utils/dicts. Connect to GitMCP for repo ops and Context7 for model context.
npx claudepluginhub sciris/scirisUse when working with advanced Sciris features — nested dictionaries (sc.makenested, sc.getnested, sc.setnested, sc.iternested, sc.search, sc.iterobj), context blocks (sc.capture, sc.tryexcept), sc.smoothinterp interpolation, sc.asd optimization, sc.animation, sc.savemovie, or sc.printjson.
Use when working with NumPy arrays in Sciris — finding indices, nearest values, concatenation, handling NaN/missing values, smoothing data, 2D Gaussian smoothing, or linear regression with sc.findinds, sc.findnearest, sc.cat, sc.rmnans, sc.fillnans, sc.smooth, sc.rolling, sc.linregress.
Use when working with dates, times, or timing in Sciris — sc.timer, sc.tic, sc.toc, sc.date, sc.daterange, sc.datedelta, sc.now, sc.getdate, sc.time, sc.timedsleep, sc.randsleep, date format conversion, or timing code blocks.
Use when working with Sciris dictionaries or dataframes — sc.odict, sc.objdict, sc.dataframe, integer indexing of dicts, enumitems, object-syntax access, dataframe creation with dtypes, appendrow, or sc.dataframe.cat.
Use when saving or loading files with Sciris — sc.save, sc.load, sc.savejson, sc.loadjson, sc.saveyaml, sc.readyaml, sc.savearchive, sc.loadarchive, sc.savefig, sc.loadmetadata, sc.getfilelist, sc.thispath, sc.makefilepath, sc.rmpath, sc.metadata, sc.compareversions, sc.require, or version/reproducibility tracking.
Use when the user needs to implement a basic Sciris features — finding array values, plotting with date formatting, objdict containers, saving/loading objects, or parallelization.
Use when parallelizing code or profiling performance with Sciris — sc.parallelize, sc.Parallel, iterarg, iterkwargs, maxcpu, maxmem, async parallelization, sc.profile, sc.benchmark, sc.memload, sc.checkram, line profiling, or CPU/memory monitoring.
Use when plotting with Sciris or Matplotlib — sc.options, sc.dateformatter, sc.commaticks, sc.SIticks, sc.boxoff, sc.setylim, sc.figlayout, sc.getrowscols, sc.vectocolor, sc.gridcolors, sc.scatter3d, sc.savefig, plot styles (sciris.simple, sciris.fancy), colormaps (parula, orangeblue), or 3D plotting.
Use when printing or formatting output with Sciris — sc.heading, sc.printgreen, sc.printblue, colored output, sc.strjoin, sc.newlinejoin, sc.pr, sc.prettyobj, sc.indent, sc.progressbar, sc.printmedian, or monitoring loop progress.
Use when working with Sciris miscellaneous utilities — sc.mergedicts, sc.mergelists, sc.tolist, sc.toarray, sc.isnumber, sc.suggest, sc.download, sc.runcommand, sc.importbypath, sc.loadtext, sc.help, sc.traceback, sc.autolist, sc.pp, or type checking/conversion.
Structured AI-enabled research workflows for software development: Research, Plan, Experiment, Implement
External network access
Connects to servers outside your machine
Share bugs, ideas, or general feedback.
MCP server for advanced data visualization and plotting operations
Multi-agent workflow framework for building, testing, and shipping statistical software packages
Development environment setup: git worktrees, terminal optimization
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Persistent memory system for Claude Code - seamlessly preserve context across sessions