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.

This skill provides comprehensive strategies for handling rate limits when interacting with the Webflow Data API v2. It covers using SDK built-in retries, implementing custom exponential backoff with jitter, controlling concurrency using request queues, and optimizing calls with bulk endpoints (e.g., createItemsBulk). Use this guide when encountering 429 errors or when maximizing API throughput is critical for robust applications.

This guide provides comprehensive troubleshooting and error handling documentation for integrating the Wispr Flow voice-to-text API. It covers common issues across WebSocket streaming, REST API calls, and general dictation workflows. Users will learn how to address errors like 'Unauthorized' keys, network disconnections, and poor accuracy by utilizing best practices for context setting and API reconnection strategies.

This workflow provides comprehensive guidance for integrating the Wispr Flow voice-to-text API. It supports both low-latency WebSocket streaming and simpler REST API calls. It is essential for developers building sophisticated, voice-powered applications, including real-time dictation, transcribing content, and integrating voice inputs into core development tools.

This core workflow provides comprehensive guidance for integrating the Wispr Flow voice-to-text API. It supports both low-latency WebSocket streaming and standard REST API calls. Use this when building voice-powered applications, real-time dictation tools, or systems that require high accuracy in transcribing complex content like code, CLI commands, and technical jargon.

This debug bundle provides comprehensive guidance for integrating the Wispr Flow voice-to-text API. It covers best practices for various integration methods, such as low-latency WebSocket streaming and standard REST API calls. It is essential for developers building sophisticated voice-powered applications, dictation tools, or any system requiring robust speech recognition and error handling.

This guide demonstrates how to integrate Wispr Flow for robust voice-to-text transcription. It covers two primary methods: asynchronous REST calls for transcribing audio files, and real-time WebSocket streaming for live microphone input. Wispr specializes in developer-context-aware dictation, making it ideal for building complex voice-powered applications, especially those involving code or technical jargon.

A comprehensive guide for integrating the Wispr Flow voice-to-text API using webhooks. This skill covers best practices for real-time speech recognition, including low-latency WebSocket streaming and robust REST API calls. It is essential for developers building voice-powered applications, dictation tools, or any system requiring advanced audio processing and context-aware transcription.

This skill provides a mechanism to execute TypeScript scripts using tsx, enabling fetching and streaming responses from external HTTP endpoints. It is designed for users who need a lightweight Node.js helper utility to manage simple network API calls, making it ideal for rapid integration and data fetching tasks.

A critical discipline for managing expenses when integrating paid AI or inference APIs. This guard treats dollar cost as a third complexity dimension, mandating the definition of cost contracts (max calls per run, max budget per run, max budget per day). It enforces best practices for bounding loops, retries, and fan-out, ensuring that code bugs cannot lead to unexpected overspending. Best practice requires configuring hard caps both in the code and at the provider dashboard for defense in depth.

This skill validates the correctness and completeness of any API request. It rigorously checks the HTTP method, URL structure, required headers, body format, authentication details, and query parameters. Use it to debug cURL commands, verify endpoint calls, or ensure API structures adhere to best practices, providing immediate, actionable feedback on required fixes.

This comprehensive skill provides deep integration with Jira, enabling users to manage the entire issue lifecycle. Features include retrieving ticket details, extracting testable requirements and acceptance criteria, updating issue status (transitions), adding comments, and linking code artifacts (PR/MR). Supports both recommended MCP server approach and direct REST API calls for robust development workflow automation.