Total 44,103 skills
Showing 12 of 44103 skills
Async job processing with validated state transitions, progress tracking, and asset linking. Ensure jobs always reach terminal states with proper error handling.
Implement the circuit breaker pattern to prevent cascade failures in distributed systems. Use when adding resilience to API clients, external service calls, or any operation that can fail and should fail fast.
Centralized environment variable management with validation. Fail fast at startup if config is invalid. Supports multi-environment setups (dev/staging/prod) with type-safe access.
This skill should be used when the user wants to "create a skill", "add a skill to plugin", "write a new skill", "improve skill description", "organize skill content", or needs guidance on skill structure, progressive disclosure, or skill development best practices for Claude Code plugins.
Template-based AI prompt engine with YAML templates, brand kit injection, input sanitization for security, and token-efficient context blocks.
Daily compression of time-series data with merge logic for multiple pipeline runs, structured aggregation for dashboards, and storage estimation for capacity planning.
Optimize web performance: Core Web Vitals (LCP, CLS, INP), bundle size, images, caching. Use when site is slow, optimizing for Lighthouse scores, reducing bundle size, fixing layout shifts, or improving Time to Interactive. Triggers on: web performance, Core Web Vitals, LCP, CLS, INP, FID, bundle size, page speed, slow site.
Cloud storage integration with signed URLs, visibility control, multi-tenant path conventions, and presigned uploads for direct client uploads.
Redis-backed SSE stream management with stream registry, heartbeat monitoring, completion store for terminal events, and automatic orphan cleanup via background guardian process.
Analyzes events through historical lens using source analysis, comparative history, periodization, causation, continuity/change, and contextualization frameworks. Provides insights on historical patterns, precedents, path dependency, and long-term trends. Use when: Understanding historical context, identifying precedents, analyzing change over time, comparative history. Evaluates: Causation, continuity, change, context, historical parallels, long-term patterns.
A high-level interactive graphing library for Python. Ideal for web-based visualizations, 3D plots, and complex interactive dashboards. Built on plotly.js, it allows users to zoom, pan, and hover over data points in a browser-based environment. Use for interactive charts, web applications, Jupyter notebooks, 3D data visualization, geographic maps, financial charts, animations, time-series analysis, and building production-ready dashboards with Dash.
State-of-the-art Machine Learning for PyTorch, TensorFlow, and JAX. Provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio. The industry standard for Large Language Models (LLMs) and foundation models in science.