Skill UI

A comprehensive guide to creating a robust API versioning strategy document. It helps service teams define consistent rules for evolving their APIs over time, covering versioning schemes (URL path, headers), lifecycle policies (Stable, Deprecated, Sunset), and classifying breaking changes. Essential for maintaining backward compatibility and managing API deprecation.

This skill generates a comprehensive Technology Radar document following the ThoughtWorks format. It provides a structured framework for an engineering team to evaluate and categorize all significant technologies (tools, languages, platforms, techniques) into four quadrants (Adopt, Trial, Assess, Hold). It helps establish a shared, explicit technology strategy, detailing adoption rationales, decision trails, and maintenance processes for consistent engineering choices.

This skill generates a comprehensive and structured test strategy document. Given a feature specification, PRD, or system description, it systematically outlines the test scope, performs a detailed risk assessment, defines necessary test types (Unit, E2E, Performance, Security), and provides a prioritized, actionable test case outline to ensure robust quality assurance before release.

This guide details advanced strategies for publishing technical content across major developer platforms like Dev.to and Hashnode. It covers cross-posting best practices, canonical URL management for optimal SEO, and platform-specific optimization (e.g., tagging, content performance) to maximize reach and build authority.

This skill guides the implementation of advanced SEO strategies tailored specifically for technical audiences and developers. It covers specialized techniques such as optimizing for error messages, researching high-intent technical long-tail keywords, creating structured how-to guides, and developing objective tool comparison content. Use this when targeting developers who search with precise technical intent, needing solutions that go beyond standard documentation.

A comprehensive strategy for regression testing in AI-assisted development. It focuses on identifying systematic blind spots, such as schema inconsistencies between sandbox and production paths, and integrating automated bug checks into the development workflow. This guide teaches how to build robust, database-free API tests to ensure code quality when AI models contribute to the codebase.

Implements a robust caching strategy by using the SHA-256 hash of file content as the primary key, instead of the file path. This pattern is essential for high-cost file processing pipelines (like OCR, PDF parsing) because it ensures cache hits survive file renaming or moving, while still automatically invalidating entries when the content changes. It adheres to the Single Responsibility Principle (SRP) by isolating caching logic into a service layer wrapper.