Skill UI

This skill guides the definition of comprehensive API contracts, serving as the shared interface specification between backend and frontend services. It covers defining request/response schemas, endpoint routes, TypeScript interfaces, and standardized error handling. Use it when establishing, modifying, or documenting the interaction points between different system components to ensure seamless integration and type consistency.

This skill guides the definition of comprehensive API contracts, serving as the shared interface specification between backend and frontend services. It covers defining request/response schemas, endpoint routes, TypeScript interfaces, and standardized error handling. Use it when establishing, modifying, or documenting the interaction points between different system components to ensure seamless integration and type consistency.

This skill details the architecture and implementation of a robust API Gateway, serving as the single entry point for multiple backend microservices. It centrally manages critical cross-cutting concerns, including path-based and header-based routing, JWT/OAuth2 authentication, rate limiting, load balancing, and circuit breaker protection. This pattern is essential for building resilient, scalable, and maintainable microservices architectures, significantly simplifying client integration and request management.

A comprehensive guide to implementing robust, multi-layered API response caching using distributed stores like Redis and Memcached, alongside CDN integration. Learn advanced strategies such as tag-based cache invalidation, read-through/write-through patterns, TTL management, and serving stale-while-revalidate content to drastically boost application performance and scalability.

This guide provides comprehensive strategies for implementing privacy-safe analytics using PostHog. It addresses critical compliance requirements like GDPR and CCPA, covering explicit consent management (opt-in/opt-out), real-time property sanitization (stripping PII like IP or tokens), and methods for handling Data Subject Access Requests (SAR) and the Right to Erasure. Use this to build highly compliant and privacy-preserving analytics pipelines.

Serve production-grade LLM APIs with vLLM, leveraging PagedAttention, continuous batching, quantization, and tensor parallelism to maximize throughput while keeping latency, GPU usage, and scalability under control for OpenAI-compatible deployments.

SkyPilot orchestrates ML training, batch jobs, and serving across 20+ clouds with automatic cost-aware region selection, spot-instance recovery, managed clusters, and GPU-aware distributed training, letting you optimize spend and avoid vendor lock-in.

A comprehensive guide to implementing fault-tolerant patterns for Vercel serverless functions. Learn how to build resilient APIs using Circuit Breakers to handle external dependency failures, implementing Exponential Backoff for retries, and achieving Graceful Degradation by serving stale cache data. Essential for production-grade, highly available serverless architecture.

Guides execution of implementation plans by dispatching isolated subagents per task, enforcing a spec-first then quality review loop, and preserving overall coordination context for faster, high-quality iterations.

This skill provides a robust and safe mechanism for updating SpecKit templates and configurations from GitHub. It is designed to automatically apply the latest changes while meticulously preserving any existing project customizations, ensuring a non-disruptive workflow. It features a conversational, two-step approval process, guiding the user through the update process, reporting conflicts, and handling fresh installations gracefully. Ideal for developers needing reliable, version-controlled updates to their SpecKit environment.

This skill is intended for Perl testing functionalities. Currently, the Japanese translation and content are under development, serving as a placeholder. Users should refer to the original English skill file for the core functionality and detailed implementation.

This pipeline provides an automated solution for processing raw Indicators of Compromise (IOCs) from various sources, including IPs, domains, URLs, and emails. It performs crucial steps such as normalization, deduplication, and defanging (modifying indicators to prevent accidental execution while preserving readability). The final, processed data is converted into the standardized STIX 2.1 format and can be securely distributed via TAXII servers or MISP instances, streamlining threat intelligence sharing.