Plugins
10 pluginscurated
Component Spec and Pattern Library
Document component anatomy, variants, and usage patterns for consistent implementation.
5 skills · plugin
@alunadev
Ald Skills
Adrian Luna Díaz personal skill library — product management, engineering, design, and operations skills.
57 skills · plugin
curated
Create Design System Documentation
Generate component specifications, pattern library entries, and design system documentation for UI consistency.
8 skills · plugin
@fradser
Code Context
Retrieve code context for any repo, library, or natural-language query via DeepWiki, Context7, Exa, git clone, and web search+fetch
2 skills · plugin
@atc-net
Atc
ATC.NET library skills including atc-net tools, e.g. REST API source generation from OpenAPI specs, WPF controls, cross-platform XAML development etc.
2 skills · plugin
@brycewang-stanford
FSE Skills
Twelve FSE-specific skills for the ACM Foundations of Software Engineering conference and its PACMSE journal-style publication model, grounded in the FSE 2026/2027 researchr calls, PACMSE journal pages, ACM Digital Library, and dblp.
2 skills · plugin
@brycewang-stanford
IMC Skills
Twelve IMC-specific skills for the ACM Internet Measurement Conference, the SIGCOMM-sponsored empirical measurement flagship, grounded in the IMC 2026 call for papers, submission instructions, committees page, SIGCOMM/IMC event pages, the ACM Digital Library, and dblp.
2 skills · plugin
@brycewang-stanford
HRI Skills
Twelve HRI-specific skills for the ACM/IEEE International Conference on Human-Robot Interaction and its interdisciplinary, human-subjects-centered evidence culture, grounded in the HRI 2026/2027 calls, humanrobotinteraction.org, the ACM Digital Library, IEEE Xplore, and dblp.
2 skills · plugin
@brycewang-stanford
ASE Skills
Twelve ASE-specific skills for the IEEE/ACM International Conference on Automated Software Engineering and its automated-SE research track, grounded in the ASE 2025/2026 researchr calls, the ase26.hotcrp.com submission site, IEEE Xplore, the ACM Digital Library, and dblp.
3 skills · plugin
@brycewang-stanford
DAC Skills
Twelve DAC-specific skills for the ACM/IEEE Design Automation Conference (the Chips to Systems Conference) and its double-blind Research Manuscript track, grounded in the DAC 2026 (63rd) call, dac.com, IEEE CEDA, ACM SIGDA, the ACM Digital Library, and dblp.
2 skills · plugin
Results for “library”
48 skills
inskillflow polars
Fast 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.
1
iamanacarolinarezende polars
Fast 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.
0
doriangallo polars
Fast 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.
1
mmehdi0606 polars
Fast 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.
2
francostino polars
Fast 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.
63
arjumaan polars
Fast 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.
1
26bb polars
Fast 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.
0
sickn33 polars
Fast 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.
45.1k
mit-network polars
Fast 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.
2
chen-yu-hao cocoindex
Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.
5 · bundle
fukukei23 lead-magnets
When the user wants to create, plan, or optimize a lead magnet for email capture or lead generation. Also use when the user mentions "lead magnet," "gated content," "content upgrade," "downloadable," "ebook," "cheat sheet," "checklist," "template download," "opt-in," "freebie," "PDF download," "resource library," "content offer," "email capture content," "Notion template," "spreadsheet template," or "what should I give away for emails." Use this for planning what to create and how to distribute it. For interactive tools as lead magnets, see free-tools. For writing the actual content, see copywriting. For the email sequence after capture, see emails.
0 · bundle
alterlab-ieu alterlab-seaborn
Builds statistical plots with the seaborn Python library and pandas DataFrame integration, on attractive matplotlib-based defaults. Use for quick exploration of distributions, relationships, and categorical comparisons — box plots, violin plots, swarm/strip plots, KDE/histograms, pair plots, joint plots, regression plots, correlation heatmaps, and faceted small multiples (relplot/displot/catplot/lmplot). For interactive/hover/zoom charts defer to alterlab-plotly; for exact journal/manuscript styling (column widths, point fonts, CMYK, vector export) defer to alterlab-scientific-viz; for low-level custom matplotlib figures defer to alterlab-matplotlib (seaborn integrates with it for fine-tuning). Part of the AlterLab Academic Skills suite.
60 · bundle