Remove AI-generated jargon and restore human voice to text

This sop guides you through the process of transforming a rough idea into a detailed design document with an implementation plan and todo list. It follows the Prompt-Driven Development methodology...

Generate comprehensive API endpoint tests for REST and GraphQL APIs.

Help users build software using AI coding tools. Use when someone is using AI to generate code, building prototypes without deep technical skills, or exploring how non-engineers can create...

Consumer-driven contract test specifications (Pact, Spring Cloud Contract)

Write comprehensive end-to-end tests using Playwright with page object

Use when bumping ralph-orchestrator version for a new release, after fixes are committed and ready to publish

A library for snapshot testing in Swift with support for views, images, and custom formats

MCP server and Claude plugin for Postgres skills and documentation. Helps AI coding tools generate better PostgreSQL code.

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Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.

Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.

Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.

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Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots,...

Use when discovering codebase patterns, making architectural decisions, solving recurring problems, or learning project-specific context that should persist across sessions

Guide for AI Agents and LLM development skills including RAG, multi-agent systems, prompt engineering, memory systems, and context engineering.

Execute comprehensive disaster recovery tests, validate recovery procedures, and document lessons learned from DR exercises.

Implement code from a GitHub issue specification. Explores codebase, researches docs, creates temporary implementation plan, then implements incrementally (small piece → test → commit → next)....