Skill UI

This skill provides advanced techniques for robust prompt engineering within LangChain applications. It solves common production issues, such as f-string template breakage when user input contains literal curly braces, and guides developers on consolidating scattered prompts. Crucially, it details how to use the LangSmith Prompt Hub to version, pin, and A/B test prompts using immutable commit hashes, ensuring stable, reproducible LLM deployments.

A comprehensive skill for generating high-quality AI images and videos using advanced models like Seedance 2.0, Kling 3.0, and Midjourney. It supports diverse workflows including text-to-image, image-to-video, and video continuation. The system handles asynchronous generation, robust delivery, and multi-channel integration (e.g., Feishu, Slack), making it ideal for creative content production and automated media workflows.

This assistant functions as a professional prompt engineer, specializing in generating highly optimized, production-ready prompts for diverse AI platforms. It analyzes user intent and technical requirements across nine dimensions (Task, Context, Format, etc.), then tailors the prompt structure, constraints, and tone specifically for the target model (e.g., GPT-5.x, Claude, Gemini, Midjourney). Use it when you need to convert a vague idea into a structured, high-performing command for any large language model or generative AI tool.

This skill provides a development loop for RunwayML, an advanced creative AI platform. It allows users to programmatically generate high-quality videos from images or text prompts using the Python SDK. Ideal for integrating Runway's capabilities into local development workflows, enabling advanced creative video production, editing, and media manipulation.

This skill provides implementation patterns for using the Runway SDK. It enables users to perform advanced creative AI tasks, such as generating videos from text prompts or converting images to video, using the official Python SDK. It covers the full workflow, including setup, task execution, output retrieval, and error handling, making it ideal for creative media automation and advanced video production workflows.

This workflow guides users through the complete lifecycle of customizing large language models (LLMs). It covers uploading training data, initiating fine-tuning jobs, monitoring training progress, managing model versions, and finally deploying the optimized model to a dedicated, autoscaling inference endpoint using the Together AI API. Ideal for production-level customization.

This skill provides a production-grade, containerized integration service for connecting to the Together AI platform. It facilitates high-performance inference, fine-tuning, and model deployment across over 100 open-source models using Together's OpenAI-compatible API. Includes comprehensive Docker setup, environment variable management, health checks, and zero-downtime rolling update strategies for robust, real-time LLM serving.

This comprehensive checklist guides the operational setup (MLOps) for AI applications using Together AI's OpenAI-compatible API. It covers critical production concerns, including secure API key management, implementing robust rate limit handling, building error resilience features (circuit breakers, exponential backoff), and setting up comprehensive monitoring for latency, cost control, and model availability. Essential for reliable, scalable LLM deployment.

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).

A comprehensive audio generation skill designed for professional multimedia content creation. It handles three types of audio output: music (jingles, beds), voiceovers (TTS), and sound effects (SFX). The skill intelligently routes requests to advanced models like Suno V5, Udio, MiniMax TTS, and ElevenLabs, producing a single, high-quality MP3 or WAV file ready for use in marketing, video, or podcast production.

A rigorous, Chief AI Officer-level interrogation tool designed to pressure-test any plan involving artificial intelligence. Before deployment, it forces comprehensive review across crucial dimensions: evaluation metrics, hallucination risk, EU AI Act compliance, model architecture selection (API vs. build), cost economics, and required organizational roles. Essential for maintaining AI product safety and compliance.