Skill UI

A comprehensive workflow guide for fine-tuning open-source Large Language Models (LLMs) using the Together AI API. This process covers preparing structured training data (JSONL format), uploading the file, initiating the fine-tuning job, monitoring the training status, and finally deploying the custom model for inference. Ideal for developers needing to customize models for specific enterprise tasks, such as customer support or specialized content generation.

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 internal agent skill defines the structured procedure for displaying bug triage results in terminal markdown format. It generates comprehensive summaries of bug clusters, provides detailed views of evidence and reports, and handles the parsing and execution flow for user review commands (e.g., `details`, `file`, `dismiss`, `escalate`). It is a core component for automated bug triage and defect management workflows.

This guide details the process of deploying and configuring the WizTelemetry Data Pipeline using Vector. It is essential for establishing data collection, transformation, and routing capabilities for comprehensive observability data, including logs, auditing records, events, and notifications within a Kubernetes environment.

A comprehensive solution for migrating large volumes of content into Webflow CMS. This deep dive guide facilitates data transfer from diverse source formats—including WordPress, Contentful, Strapi, CSV, and JSON—using the Webflow Data API v2. It covers essential steps like target schema assessment, data transformation, bulk importing (100 items/batch), and robust data validation, making large-scale platform replatforming manageable.

This guide details how to implement custom Content Management System (CMS) field types within a framework. It covers extending the core DataFieldBuilder, composing complex validator interfaces, creating a dedicated FieldTypeFactory, and ensuring proper registration via Dependency Injection (DI) and module augmentation for full TypeScript autocomplete support. Essential for adding fields with specialized validation or storage formats.

Provides comprehensive guidance for optimizing the performance of the Wispr Flow voice-to-text API. This skill covers best practices for integrating dictation, streaming, and building robust voice-powered applications. It details optimal WebSocket usage, recommended audio formats (16kHz PCM), context setting for specialized fields like programming, and robust error handling strategies (e.g., 401 Unauthorized, network disconnects).

This guide provides the reference architecture and best practices for integrating Wispr Flow's voice-to-text API. It details how to utilize both WebSocket (for low-latency streaming) and REST APIs, covering essential concepts like audio format requirements, context awareness (especially for programming code), and comprehensive error handling strategies.

This pattern provides comprehensive guidance for integrating the Wispr Flow voice-to-text API. It covers best practices for both low-latency WebSocket streaming and simpler REST API usage. Key topics include authentication, recommended audio formats, robust error handling, and context awareness (e.g., understanding code or CLI commands), making it ideal for building advanced voice-powered applications.

A comprehensive guide for migrating and integrating with the Wispr Flow voice-to-text API. This skill details best practices for both WebSocket (low-latency streaming) and REST API methods. It covers authentication, optimal audio formatting (16kHz mono PCM), context awareness for specialized jargon (e.g., code), and robust error handling across multiple platforms (Mac, iOS, browser).

This tool allows users to execute complex, multi-agent workflows defined in YAML format directly within the AI environment. It functions as an orchestration engine, sequentially invoking various specialized roles (agents) without requiring manual API key configuration. Ideal for structured tasks requiring collaboration between multiple personas.

This guide provides detailed instructions on configuring API access for Workhuman, utilizing the OAuth 2.0 protocol. It is essential for integrating external Human Resources Information Systems (HRIS) or building custom workflows for employee recognition and rewards management. Users will learn how to obtain access tokens and programmatically interact with Workhuman's social recognition features.