Ralph Orchestrator implements the simple but effective "Ralph Wiggum" technique for autonomous task completion, continuously running an AI agent against a prompt file until the task is marked as complete or limits are reached. This implementation provides a robust, well-tested, and feature-complete orchestration system for AI-driven development. Also cited in the Anthropic Ralph plugin documentation.
A development environment for Claude Code with a spec-driven workflow, TDD enforcement, cross-session memory, semantic search, quality hooks and modular rules. Large, with wide coverage.
Hand-crafted collection of advanced context engineering techniques and patterns with minimal token footprint focused on improving agent result quality.
Enables users to prompt codex from claude code. Unlike the raw codex mcp server, this skill infers parameters such as model, reasoning effort, sandboxing from your prompt or asks you to specify them. It also simplifies continuing prior codex sessions so that codex can continue with the prior context.
Workflow automation system for Claude with a group of useful plugins, agents, and skills. Automates task-to-production workflows, PR management, code cleanup, performance investigation, drift detection, and multi-agent code review. Includes agnix for linting agent configurations. Built on thousands of lines of code with thousands of tests. Uses deterministic detection (regex, AST) with LLM judgment for efficiency. Used on many production systems.
A Claude Code plugin that provides an autonomous AI copywriter: research agents gather market knowledge into custom knowledge bases, and a Ralph loop writes the copy.