Skill UI

A comprehensive reference architecture for building scalable, cost-effective, and robust AI services. This system manages the full AI lifecycle, including intelligent model routing (for quality/cost trade-offs), response caching (using Redis), asynchronous batch processing, and fine-tuning pipeline management via Together AI's OpenAI-compatible API. Ideal for enterprise applications requiring high availability across multiple open-source models.

A comprehensive guide to implementing production-ready patterns for interacting with the Together AI API. This includes a singleton client for seamless OpenAI-compatible integration, robust error wrappers with retry logic, and a fluent request builder. It covers best practices for LLM inference, model setup, and handling diverse response types (chat, embedding, fine-tuning).

This guide covers essential security best practices for utilizing Together AI's OpenAI-compatible API for inference, fine-tuning, and model deployment. It provides code examples and architectural advice on secure API key management, robust webhook signature verification, input validation using schemas (like Zod), and implementing data redaction pipelines to protect sensitive information in logs and datasets. Essential for building secure AI applications.

This guide provides comprehensive strategies for migrating applications using the Together AI platform. It addresses common issues like model ID deprecations, API schema changes (for fine-tuning or chat completions), and best practices for robust inference and deployment using their OpenAI-compatible API.

This skill guides a systematic process for debugging reported issues. It explores the codebase to identify the root cause, traces the code path, and then generates a comprehensive GitHub issue. The fix plan strictly follows the Test-Driven Development (TDD) Red-Green cycle, ensuring proposed solutions are robust and durable, surviving major refactors.

This technique is used to locate a specific TV series by leveraging the known filmography of its creator (director, writer, or showrunner). When the question provides clues that the creator also worked on a distinct, identifiable project (e.g., a trilogy or an award-winning miniseries), use that secondary work as a powerful search anchor. Identify the person first using their other works, then trace back through their complete credits to pinpoint the target series.

This guide outlines best practices and structured workflows for automating complex tasks within the Unity Editor using the Model Context Protocol (MCP). It provides programmatic methods for managing GameObjects, applying script edits, analyzing the editor state, executing batch commands, and capturing detailed, multi-view screenshots. Ideal for developers needing robust, repeatable, and automated testing or operational tasks within Unity projects.

unslop is a powerful command-line interface (CLI) tool designed for post-processing text. It programmatically strips out common and identifiable patterns associated with AI-generated writing. Use it as a final, deterministic pass before publishing documentation, blog posts, or any content derived from large language models (LLMs), ensuring a more natural and human-like tone.

This skill provides a structured framework for capturing, organizing, and maintaining persistent facts about the user. By segmenting facts into topic-specific files (e.g., coding preferences, tech stack, goals), it creates a reliable, objective knowledge base. This structure is crucial for AI agents and applications to achieve highly personalized interactions and provide accurate context.

This skill provides enterprise-grade observability patterns specifically for Veeva Vault deployments. It guides users through implementing advanced patterns, utilizing VQL for efficient data retrieval, and ensuring compliance in regulated life sciences environments. Use this when building robust, observable applications within the Veeva ecosystem.

This comprehensive guide teaches how to use httpYac in VSCode to convert API documentation (like Swagger or Postman collections) into robust, executable .http files. It provides advanced workflow guidance for implementing complex authentication schemes (OAuth2, Bearer), managing multi-environment configurations, chaining requests using response data, and integrating testing workflows with CI/CD pipelines for professional-grade API automation.

This guide details how to configure the VS Code Port Monitor extension. It allows developers to monitor the port status (in use or free) for development servers (like Vite, Next.js) and databases in real time directly on the status bar. Use this skill to set up multi-service or full-stack development environments, prevent port conflicts, and troubleshoot running services.