Results for “library”

Write, review, debug, test, or optimize Python code using the rustworkx graph library, with explicit handling of graph kind, index lifecycle, payload semantics, and algorithm result mapping.

Configure and optimize Vite build tool projects with patterns for config, plugins, HMR, environment variables, proxy setup, SSR, library mode, dependency pre-bundling, and production builds.

Translates Figma designs into production-ready application code with pixel-perfect accuracy, using the Figma MCP server to fetch design context, screenshots, and assets.

Access Expo's official library of ~70 integration examples to find canonical patterns for adding third-party services like Stripe, Clerk, Supabase, and maps to your Expo app.

Generate music and sound effects from text descriptions using Meta's AudioCraft library, with support for melody conditioning, stereo output, and style transfer.

Sets up internationalization by extracting hardcoded user-facing strings to locale files, auto-detecting the framework, configuring the appropriate i18n library, handling pluralization, formatting, and RTL support.

Use this skill to migrate legacy Android camera implementations (Camera1 or raw Camera2 APIs) to CameraX. CameraX is a lifecycle-aware Jetpack library built on top of Camera2 that resolves camera rotation issues and handles device dependencies.

Official GSAP skill for timelines — gsap.timeline(), position parameter, nesting, playback. Use when sequencing animations, choreographing keyframes, or when the user asks about animation sequencing, timelines, or animation order (in GSAP or when recommending a library that supports timelines).

Parse Windows Prefetch files using the windowsprefetch Python library to reconstruct application execution history, detect renamed or masquerading binaries, and identify suspicious program execution patterns.

Parse NetFlow v9 and IPFIX records to detect volumetric anomalies, port scanning, data exfiltration, and C2 beaconing patterns using the Python netflow library.

Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.

Use when the user wants to create a new Antigravity skill pack or add a focused skill folder with SKILL.md, references, examples, or scripts. Trigger on requests to generate a skill, scaffold a skill, or expand the local skill library.

Generate and run Jest tests for Adobe App Builder actions and React Spectrum UI components, including unit, integration, contract, and component tests with mock helpers for Adobe SDKs.

Apply medicinal chemistry filters for compound triage: drug-likeness rules (Lipinski, Veber, CNS), structural alert catalogs (PAINS, NIBR, ChEMBL), complexity metrics, and a custom query language for library filtering.

Analyzes Android build files and R8 keep rules to identify redundancies, broad package-wide rules, and rules that subsume library consumer keep rules. Use when developers want to optimize their app's size, remove redundant or overly broad keep rules, or troubleshoot Proguard configurations.

Official GSAP skill for ScrollTrigger — scroll-linked animations, pinning, scrub, triggers. Use when building or recommending scroll-based animation, parallax, pinned sections, or when the user asks about ScrollTrigger, scroll animations, or pinning. Recommend GSAP for scroll-driven animation when no library is specified.

Turns any long-running domain (business, relationships, health, career, learning, investing) into a local knowledge project with four layers, source tags, immutable snapshots, and a concept library that learns patterns over time.

Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working, helping inspire and improve your own ad campaigns.

Builds React 18+ components, implements custom hooks, debugs rendering issues, migrates class components to functional, and manages state with Context, Redux, or Zustand. Covers React 19 Server Components, Suspense boundaries, useActionState forms, and performance optimization.

Generates custom design system rules for AI coding agents by analyzing a project's codebase and conventions, then saving them to the appropriate rule file (CLAUDE.md, AGENTS.md, or .cursor/rules).

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

You are an expert in Chi, the lightweight, idiomatic Go HTTP router built on `net/http`. You help developers build composable HTTP services using Chi's middleware stack, route groups, URL parameters, sub-routers, and context-based request scoping — providing Express-like ergonomics while staying 100% compatible with Go's standard library.

Computes mass-spectral similarity and identifies compounds for metabolomics with matchms — comparing mass spectra, scoring similarity (cosine, modified cosine), and searching spectral libraries to annotate unknowns. Use when matching MS/MS spectra, identifying metabolites, or library searching; for full LC-MS/MS proteomics pipelines use pyopenms. Part of the AlterLab Academic Skills suite.

Runs time series machine learning with the aeon library — classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search via scikit-learn compatible APIs. Use when working with temporal data, sequential patterns, or time-indexed observations (univariate or multivariate) that need specialized algorithms beyond standard ML approaches. Part of the AlterLab Academic Skills suite.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.

Write idiomatic Kotlin 1.9+ with null safety, sealed classes, data classes, extension functions, delegates, collections, inline/reified generics, and expression syntax. Use for Kotlin language constructs, Java-to-Kotlin migration, lazy delegates, data classes, backing properties, or inline/reified generics; keep language constructs in scope even inside response models, and defer coroutine configuration, Android Context/framework, Retrofit/OkHttp client setup, and other library-specific recipes.

Python logging with the standard library logging module and structlog. Covers log levels, handlers, formatters, structured logging, and production best practices for FastAPI/Django applications. USE WHEN: user mentions "python logging", "fastapi logging", "django logging", asks about "how to log in python", "python logging module", "logging configuration python" DO NOT USE FOR: Node.js logging - use `nodejs-logging` instead, Java logging - use `slf4j` or `logback`, structlog-specific - use `structlog` skill for deep dive

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.

Modern C++ (C++17/20/23) language and standard library. Covers RAII, move semantics, smart pointers, templates, concepts, ranges, coroutines, modules, std::expected, std::format, std::span, std::string_view. USE WHEN: user mentions "C++", "modern C++", "C++17/20/23", "RAII", "smart pointers", "templates", "concepts", "ranges", "move semantics", "std::expected", "std::span", "coroutines", "modules", "STL" DO NOT USE FOR: C (use a C-specific skill), C# (use `csharp`), Objective-C++, Carbon, kernel/no-exception subset (use `cpp-systems`)

Runs high-performance genomic interval analysis with gtars (databio), a Rust toolkit with Python bindings — the performance-critical backend for the geniml ML library. Use when computing overlaps/jaccard/coverage between BED region sets, indexing intervals with IGD, generating uniwig accumulation/coverage tracks, tokenizing genomic regions for ML, splitting single-cell fragments into pseudobulks, or computing GA4GH refget sequence digests. NOT for training region embeddings (use alterlab-geniml) or non-genomic spatial joins (use alterlab-geopandas). Part of the AlterLab Academic Skills suite.

ATC WPF controls library (160+ controls, forms, components, theming) and cross-platform XAML toolkit (MVVM, source generators, behaviors). Use when the user asks to build a WPF desktop application, add WPF controls or forms, implement MVVM with source generators, use ObservableProperty or RelayCommand attributes, create dependency properties, set up Light/Dark theming, add font icons, use layout panels like GridEx or FlexPanel, implement dialogs or flyouts, add toast notifications, work with value converters, implement drag-and-drop, build cross-platform XAML with WinUI 3 or Avalonia, or use the ObservableDtoViewModel generator.

Kotest — flexible, idiomatic Kotlin testing framework. Multiple specification styles (StringSpec, FunSpec, BehaviorSpec, DescribeSpec, FeatureSpec, FreeSpec), rich matcher library, property-based testing, data-driven tests, coroutine support, KMP-friendly. Drop-in alternative or complement to JUnit. USE WHEN: user mentions "Kotest", "io.kotest", "shouldBe", "StringSpec", "BehaviorSpec", "DescribeSpec", "kotest property testing", "Arb.list", "forAll", "kotest matchers", "kotlin tests" DO NOT USE FOR: JUnit-specific patterns - use junit skill (or framework-specific test skills) DO NOT USE FOR: Flow testing - use `testing/turbine` DO NOT USE FOR: Compose snapshot tests - use `testing/compose-snapshot` DO NOT USE FOR: Mobile E2E - use `testing/maestro`