> browse/registry

> gtars

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

> modal

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

> scikit-learn

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.

> matlab

MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter

> geopandas

Python library for working with geospatial vector data including shapefiles, GeoJSON, and GeoPackage files. Use when working with geographic data for spatial analysis, geometric operations, coordinate transformations, spatial joins, overlay operations, choropleth mapping, or any task involving reading/writing/analyzing vector geographic data. Supports PostGIS databases, interactive maps, and integration with matplotlib/folium/cartopy. Use for tasks like buffer analysis, spatial joins between dat

> geomaster

Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, cloud-native workflows (STAC, COG, Planetary Computer), and 8 programming languages (Python, R, Julia, JavaScript, C++, Java, Go, Rust) with 500+ code examples. U

> networkx

Comprehensive toolkit for creating, analyzing, and visualizing complex networks and graphs in Python. Use when working with network/graph data structures, analyzing relationships between entities, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks, or visualizing network topologies. Applicable to social networks, biological networks, transportation systems, citation networks, and any domain involving pairwise relationships.

> pydicom

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, rad

> uniprot-database

Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.

> run-python-tests

Run end-to-end Python tests after making changes to verify correctness. Use this when you want to verify your changes from an end-to-end perspective, after ensuring the build and Rust tests pass.

> manimce-best-practices

Trigger when: (1) User mentions "manim" or "Manim Community" or "ManimCE", (2) Code contains `from manim import *`, (3) User runs `manim` CLI commands, (4) Working with Scene, MathTex, Create(), or ManimCE-specific classes. Best practices for Manim Community Edition - the community-maintained Python animation engine. Covers Scene structure, animations, LaTeX/MathTex, 3D with ThreeDScene, camera control, styling, and CLI usage. NOT for ManimGL/3b1b version (which uses `manimlib` imports and `ma

> python

Python 3.11+ performance optimization guidelines (formerly python-311). This skill should be used when writing, reviewing, or refactoring Python code to ensure optimal performance patterns. Triggers on tasks involving asyncio, data structures, memory management, concurrency, loops, strings, or Python idioms.

> graph-schema

Graph database schema design and data modeling expert. Use when designing, reviewing, or refactoring graph database schemas (Neo4j, Memgraph, Neptune, etc.). Triggers on graph modeling, node/relationship design, Cypher schema, property graph design, knowledge graph modeling, or when translating a domain into a graph structure. Focuses primarily on data modeling correctness — understanding the user's goal and translating it into the right graph structure — with performance as a secondary concern.

> unrealhub-developer

UnrealMCPHub 代码库开发维护指南。面向修改 Hub 源码（Python/MCP 服务器）的开发者。触发：用户修改 UnrealMCPHub/src 下源码时激活。

> chart-generation

Use this skill for generating data-driven charts and visualizations using Python. Triggers: "create chart", "generate graph", "plot data", "visualize data", "bar chart", "line chart", "pie chart", "comparison chart", "positioning matrix", "trend chart", "market size chart", "TAM SAM SOM", "growth chart", "data visualization" Outputs: PNG/SVG chart images with accurate data representation. Used by: competitive-intel-agent, market-researcher-agent, pitch-deck-agent, review-analyst-agent

> script-example

Example skill demonstrating script execution capabilities. Use when you need to demonstrate how to execute shell, Python, or PHP scripts from within a skill.

> bptools-writer

Create, edit, and validate biology-problems bptools Python question generators and supporting YAML content. Use when requests involve authoring question scripts, updating files under problems/*-problems, tuning randomization or anti-cheat behavior, or debugging BBQ/QTI output that depends on bptools.py and qti_package_maker.

> unit-test-starter

Generate thorough Python 3 pytest unit tests across a repo by scanning every *.py file and each function, writing one test module per source file while skipping IO/network behavior and documenting gaps.

> pyside6-ui-engineer

Design, implement, refactor, and review PySide6 desktop applications with strong widget architecture, signal-slot design, state flow, and expert UI/UX logic. Use when building or fixing Qt for Python windows, dialogs, forms, navigation shells, model-view tables, theming, validation, accessibility, or interaction polish in Python GUI code.

> python-code-review

Comprehensive Python code review focused on bugs, correctness, security, maintainability, and actionable fixes. Use when a user asks for a review of Python files, wants severity-rated findings, wants before/after fix suggestions, or wants verification that implementation matches an active plan document (if one exists). Start by applying read-repo-rules to AGENTS.md, docs/REPO_STYLE.md, docs/PYTHON_STYLE.md, and docs/CHANGELOG.md so review guidance follows repository rules.