Skill UI

This skill provides comprehensive guidelines based on Clean Code principles, transforming merely functional code into highly readable, maintainable, and robust software. It covers best practices for naming conventions, function design (small, single responsibility), error handling (exceptions over return codes), formatting, and adhering to Test-Driven Development (TDD). Use this skill when writing new features, reviewing pull requests, or refactoring legacy systems to improve overall code quality.

A comprehensive guide to production-ready patterns for the Databricks Python SDK. This skill covers essential best practices including singleton client initialization, structured error handling with typed exceptions, context-managed cluster lifecycle control (ensuring cleanup), and implementing type-safe job definitions. It is essential for building robust, maintainable, and idiomatic integrations with the Databricks platform.

A comprehensive guide to diagnosing and resolving common errors encountered when using the Evernote API. It covers three main exception types—User, System, and Not Found—and provides practical solutions, including ENML validation, rate limit retry mechanisms, and safe resource retrieval patterns, ensuring robust application integration.

A comprehensive guide detailing production-ready best practices for interacting with the Evernote SDK. Covers advanced topics such as efficient search using NoteFilter, handling attachments via MD5 hashing, robust error management (rate limiting, specific exceptions), optimized batch processing, and idempotent tag/notebook management for complex applications.

This guide teaches developers how to achieve type-safe and predictable error handling in TypeScript using functional programming concepts from fp-ts, specifically focusing on the Either and TaskEither patterns. Instead of relying on disruptive try/catch exceptions, this pattern treats errors as explicit data values, forcing the calling code to handle failure paths, which is crucial for building robust, maintainable, and functional APIs and services.

This skill provides comprehensive guidance for diagnosing and resolving common Guidewire Cloud API errors. It covers typical HTTP status codes (400, 401, 403, 404, 409, 422) and common Gosu exceptions like ClassNotFoundException, NPE, and ValidationException. Use this resource when integrating with Guidewire systems or troubleshooting failed API calls.

This comprehensive guide serves as a quick reference for diagnosing and resolving common Ideogram API errors and exceptions. It covers critical issues such as authentication failures (401), rate limiting (429), safety check failures (422), and incorrect parameter formats (400). Use this resource when debugging failed image generation requests or integrating Ideogram functionality into an application.

This skill provides a comprehensive diagnostic reference for common errors and exceptions encountered with the Instantly.ai API v2. It covers critical areas including HTTP status codes (400, 401, 429, 500), campaign lifecycle issues (e.g., stuck in draft), account health checks, lead duplication handling, and implementing rate limit backoff. Use this when debugging failed API requests or troubleshooting complex campaign, account, or lead management issues.

Defines Java 17+ coding standards for Spring Boot services, covering naming, immutability, Optional usage, streams, exceptions, generics, project layout, and testing practices to ensure readable, maintainable code.

A comprehensive guide to mastering asynchronous programming using Kotlin Coroutines and Flow. Covers advanced topics such as structured concurrency, robust exception handling, and creating reactive data streams with StateFlow and SharedFlow. Essential for developing high-performance, modern Kotlin applications.

A comprehensive guide for diagnosing and fixing common Lokalise API errors and exceptions. This skill details the error response format and provides diagnostic cURL commands for specific HTTP status codes (401, 400, 404, 429, 413, 500, 503). Use it when encountering failed requests, debugging integration issues, or needing to verify API token validity and rate limit status.

A comprehensive guide for diagnosing and fixing common errors and exceptions encountered when using the Mistral AI API. Covers critical topics such as 401 Unauthorized, 429 Rate Limiting, invalid model IDs, context length limits, and server errors, providing actionable fixes and code snippets for developers.