Skill UI

Automate the Continuous Integration and Continuous Deployment (CI/CD) workflow for applications leveraging Together AI's OpenAI-compatible API. This skill sets up comprehensive GitHub Actions workflows to run unit tests (mocking completions and embeddings) on every Pull Request, and full integration tests (live API calls) upon merging to the main branch. It ensures robust validation of prompt formatting, model selection, and API connectivity for various LLMs.

A comprehensive guide to optimizing operating costs when utilizing Together AI's OpenAI-compatible API. This resource details strategies for cost reduction across various AI tasks, including inference, fine-tuning, and model deployment. Learn how to select appropriate model sizes, implement caching, leverage batch inference, and utilize Turbo variants to maximize efficiency and minimize spending.

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 guide provides a comprehensive tutorial on running various AI inference tasks using the Together AI API, which is compatible with the OpenAI standard. It demonstrates key functionalities including chat completions, streaming responses, image generation, and creating embeddings. This is ideal for developers who need to test open-source models, compare performance across different LLMs (like Llama or Mixtral), or integrate powerful generative AI features into their applications using Python or Node.js.

Provides comprehensive guidance for performance tuning, inference, and fine-tuning using the Together AI platform. This skill supports working with Together AI's OpenAI-compatible API, covering model deployment, utilizing various open-source models (like Llama, Mixtral), and implementing best practices for efficient and cost-effective batch inference.

This meta-skill establishes a rigorous and mandatory workflow for all AI agent interactions. It dictates that before generating any response, the agent must check for and invoke all relevant specialized skills, regardless of the perceived complexity or simplicity of the user request. It defines strict rules for skill prioritization, establishes user instructions as the highest authority, and outlines structured processes for various development scenarios, ensuring systematic and complete task execution.

Provides a comprehensive checklist and technical guidelines for safely deploying Webflow Data API integrations to a production environment. Covers critical areas like token security, rate limit management, implementing circuit breakers, setting up health checks, and handling various API errors to ensure reliable, high-availability service.

This guide provides comprehensive implementation details for Webflow webhooks. It covers the entire lifecycle, including registering various trigger types (form submissions, new orders, site publishing) via the API. Critically, it teaches how to set up a secure backend endpoint with HMAC signature verification, allowing users to build robust, event-driven workflows that react automatically to user actions within Webflow.

This module provides essential abstractions and hooks (BuildParam, BuildParams, useBuildParams) for managing build parameters within the administrative interface. It allows developers to centralize the definition, retrieval, and usage of configuration parameters required for the application's setup and various features, ensuring clean and type-safe access to build-time variables.

This skill provides a robust, schema-driven solution for managing and enforcing permissions in administrative user interfaces. It allows developers to define complex permission structures (the domain schema) and automatically generates associated UI forms, injectable permission checks, and component props. Use it to add granular permission controls to any admin section, supporting multi-entity, complex access scopes (e.g., full/own), and various operational actions.

This catalog provides essential TypeScript abstractions, types, and hooks for implementing robust multi-tenancy features in administrative interfaces. It helps developers manage the current tenant context, check tenant roles (e.g., root vs. non-root), and handle tenant state changes (enable/disable) across various modules. It is crucial for building scalable, secure, and multi-tenant SaaS platforms.

This skill guides developers on creating and managing Headless CMS content models programmatically using the ModelFactory pattern. It covers defining complex data structures, including various field types (text, richText, file, ref), implementing validators (required, unique), configuring layouts, and establishing relationships between models. It is essential for advanced, code-driven CMS customization and API integration.