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Found 2,040 Skills
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
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.
AWS DynamoDB single-table design, GSI patterns, SDK v3 TypeScript/Python
Python testing with pytest covering fixtures, parametrization, mocking, and test organization for reliable test suites
Practical Python craftsmanship guidance based on One Python Craftsman. Use when writing, refactoring, or reviewing Python code for naming, branching, data structures, functions, exceptions, loops, decorators, imports, file I/O, edge cases, and modern syntax choices. If the skills set includes friendly-python, suggest invoking it for better Python outcomes.
Build applications with the Letta API — a model-agnostic, stateful API for building persistent agents with memory and long-term learning. Covers SDK patterns for Python and TypeScript. Includes 24 working code examples.
Project planning and feature breakdown for Python/React full-stack projects. Use during the planning phase when breaking down feature requests, user stories, or product requirements into implementation plans. Guides identification of affected files and modules, defines acceptance criteria, assesses risks, and estimates overall complexity. Produces module maps, risk assessments, and acceptance criteria. Does NOT cover architecture decisions (use system-architecture), implementation (use python-backend-expert or react-frontend-expert), or atomic task decomposition (use task-decomposition).
Auto-generates code flow diagrams from Python module analysis. Detects when architecture diagrams become stale (code changed, diagram didn't). Use when: creating new modules, reviewing PRs for architecture impact, or checking diagram freshness. Generates mermaid diagrams showing imports, dependencies, and module relationships.
Guidance for implementing high-performance portfolio optimization using Python C extensions. This skill applies when tasks require optimizing financial computations (matrix operations, covariance calculations, portfolio risk metrics) by implementing C extensions for Python. Use when performance speedup requirements exist (e.g., 1.2x or greater) and the task involves numerical computations on large datasets (thousands of assets).
Database and HTTP connection pooling patterns for Python async applications. Use when configuring asyncpg pools, aiohttp sessions, or optimizing connection lifecycle in high-concurrency services.
Implements search and filter interfaces for both frontend (React/TypeScript) and backend (Python) with debouncing, query management, and database integration. Use when adding search functionality, building filter UIs, implementing faceted search, or optimizing search performance.
Access Airtable bases, tables, and records. Use when user mentions Airtable, bases, tables, records, or spreadsheet data. Uses Python pyairtable library for clean, reliable access.