Community Plugin

ai-eng-system

AI Engineering System with context engineering and research orchestration for Claude Code

0.2.1

Updated 7 hours ago

Capabilities

Commands

Agents

Skills

Hooks

MCP Servers

LSP Servers

Install

Add the repository(one-time)

/plugin marketplace add v1truv1us/ai-eng-ralph-cli

Install the plugin

/plugin install v1truv1us-ai-eng-system@v1truv1us/ai-eng-ralph-cli

Component Details

comprehensive-research

inherits

Multi-phase research orchestration for thorough codebase, documentation, and external knowledge investigation. Invoked by /ai-eng/research command. Use when conducting deep analysis, exploring codebases, investigating patterns, or synthesizing findings from multiple sources.

coolify-deploy

inherits

Deploy to Coolify with best practices

git-worktree

inherits

Manage Git worktrees for parallel development

incentive-prompting

inherits

Research-backed prompting techniques for improved AI response quality (+45-115% improvement). Use when optimizing prompts, enhancing agent instructions, or when maximum response quality is critical. Invoked by /ai-eng/optimize command. Includes expert persona, stakes language, step-by-step reasoning, challenge framing, and self-evaluation techniques.

plugin-dev

inherits

6 assets

This skill should be used when creating extensions for Claude Code or OpenCode, including plugins, commands, agents, skills, and custom tools. Covers both platforms with format specifications, best practices, and the ai-eng-system build system.

prompt-refinement

inherits

4 assets

Transform prompts into structured TCRO format with phase-specific clarification. Automatically invoked by /ai-eng/research, /ai-eng/plan, /ai-eng/work, and /ai-eng/specify commands. Use when refining vague prompts, structuring requirements, or enhancing user input quality before execution.

text-cleanup

inherits

2 assets

Comprehensive patterns and techniques for removing AI-generated verbosity and slop

ralph-wiggum

inherits

Continuous iteration loop pattern for well-defined tasks with clear completion criteria. Use when getting tests to pass, implementing features with automatic verification, bug fixing with clear success conditions, or running automated development overnight. Provides prompt templates, safety guidelines, and integration patterns for ai-eng-system workflows.