Skill UI

A comprehensive guide providing production-ready patterns for integrating with Salesforce using jsforce (TypeScript) and simple-salesforce (Python). These patterns cover essential topics such as implementing singleton connection management with automatic token refresh, defining typed sObject interfaces, building type-safe SOQL query builders, and wrapping API calls with robust error handling mechanisms. Ideal for developers refactoring existing Salesforce integrations or establishing standardized team coding practices.

This guide details how to deploy SerpApi-powered search functionality into production environments using modern serverless platforms like Vercel and Google Cloud Run. It critically emphasizes the security requirement: all API calls must be proxied through a secure backend endpoint and must never expose the API key to client-side browsers, ensuring robust and secure search integrations.

This guide provides detailed instructions for migrating code from the legacy `google-search-results` package to the modern `serpapi` client library. It covers major API changes, including structural updates in Python and Node.js, transitioning from callback-based or class-based calls to modern, promise/async-await structures. Use this when upgrading dependencies or updating search logic.

This wrapper integrates Shopify's official AI Toolkit MCP server with Claude Code. It provides essential developer capabilities, including real-time GraphQL schema validation, Liquid template linting (checking for deprecated filters and anti-patterns), and instant search across Shopify's extensive documentation. Use this skill when setting up complex Shopify MCP integrations, ensuring code quality, or debugging API calls.

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.