By v1truv1us
Core workflow: plan, work, review cycle with research and context engineering
npx claudepluginhub v1truv1us/ai-eng-system --plugin ai-eng-coreManage session state, memories, and context engineering
Initialize ai-eng-system configuration and project setup
Create detailed implementation plans from specifications
Conduct comprehensive multi-phase research across codebase, documentation, and external sources
Run comprehensive code review with multiple perspectives
Review recently changed files for code reuse, quality, and efficiency issues, then fix them
Create a feature specification using structured requirements gathering
Execute a plan or task with systematic tracking, quality gates, and comprehensive validation.
Architectural guidance and technical decisions
Design RESTful APIs, microservice boundaries, and database schemas. Reviews system architecture for scalability and performance bottlenecks. Use PROACTIVELY when creating new backend services or APIs.
Reviews frontend code for best practices
Generalist implementation developer focused on end-to-end feature delivery (UI → API → data) within established architectural, security, performance, and infrastructure guidelines. Provides cohesive, maintainable full-stack solutions while deferring deep specialization decisions to appropriate expert agents.
Expert Java development with modern Java 21+ features
Ensures proper delegation to ai-eng-system specialized agents. Apply before any development task. Use for routing decisions when working with ai-eng-system.
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.
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.
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.
Comprehensive patterns and techniques for removing AI-generated verbosity and slop
Review recently changed files for code reuse, quality, and efficiency issues, then fix them. Use when simplifying code, removing complexity, improving readability, or after making changes.
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.
AI engineering workflow toolkit for Claude Code and OpenCode with 42 commands, 32 specialized agents, and 12 reusable skills.
This repository ships three npm packages:
@ai-eng-system/core - shared library and content-loading helpers@ai-eng-system/toolkit - generated Claude Code, OpenCode, and marketplace assets@ai-eng-system/cli - executable installer and command-line workflowsThe repo root package is private and is never published.
npm install -g @ai-eng-system/cli
# Install commands, agents, and skills into the current project
ai-eng install --scope project
# Or install globally for OpenCode
ai-eng install --scope global
/plugin marketplace add v1truv1us/ai-eng-system
/plugin install ai-eng-system@ai-eng-marketplace
{
"$schema": "https://opencode.ai/config.json",
"plugin": ["opencode-skills", "ai-eng-system"]
}
| Phase | Command | Purpose |
|---|---|---|
| Research | /ai-eng/research | Multi-phase codebase and external research |
| Specify | /ai-eng/specify | Feature/spec generation with TCRO structure |
| Plan | /ai-eng/plan | Implementation planning |
| Work | /ai-eng/work | Guided execution with quality gates |
| Review | /ai-eng/review | Multi-agent code review |
Related commands:
/ai-eng/ralph-wiggum - iterative full-cycle workflow/ai-eng/simplify - code reuse, quality, and efficiency simplificationai-eng/ namespaceai-eng/simplify and workflow/ralph-wiggumSelected commands beyond the core workflow:
/ai-eng/create-plugin, /ai-eng/create-agent, /ai-eng/create-command, /ai-eng/create-skill, /ai-eng/create-tool/ai-eng/code-review, /ai-eng/agent-analyzer, /ai-eng/fact-check, /ai-eng/deep-research, /ai-eng/content-optimize/ai-eng/deploy, /ai-eng/docker, /ai-eng/cloudflare, /ai-eng/github, /ai-eng/k8s, /ai-eng/monitoring, /ai-eng/security-scan/ai-eng/context, /ai-eng/knowledge-capture, /ai-eng/init, /ai-eng/seoSee docs/reference/commands.md for the full command list.
The generated outputs now preserve namespaced skill paths.
Examples:
skills/ai-eng/simplify/SKILL.md -> /ai-eng/simplifyskills/workflow/ralph-wiggum/SKILL.md -> /ai-eng/ralph-wiggumskills/comprehensive-research/SKILL.md -> /ai-eng/researchSee docs/reference/skills.md for the full skill inventory.
The current coordinated release version is 0.6.0 for:
@ai-eng-system/core@ai-eng-system/toolkit@ai-eng-system/cliTrusted publishing runs through .github/workflows/publish-all-oidc.yml using GitHub OIDC.
bun install
bun run build
bun run build:toolkit
bun test
content/ Canonical command and agent docs
skills/ Canonical skill definitions
packages/core/ Published core library package
packages/toolkit/ Published toolkit assets package
packages/cli/ Published CLI package
plugins/ai-eng-system/ Marketplace plugin output
dist/ Generated root outputs
docs/getting-started/installation.mddocs/getting-started/quick-start.mddocs/reference/commands.mddocs/reference/skills.mddocs/architecture/marketplace.mdPUBLISHING.mdRELEASE.mdRELEASE_NOTES.mdBattle-tested Claude Code plugin for engineering teams — 38 agents, 156 skills, 72 legacy command shims, production-ready hooks, and selective install workflows evolved through continuous real-world use
Uses power tools
Uses Bash, Write, or Edit tools
Complete collection of battle-tested Claude Code configs from an Anthropic hackathon winner - agents, skills, hooks, rules, and legacy command shims evolved over 10+ months of intensive daily use
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
AI-supervised issue tracker for coding workflows. Manage tasks, discover work, and maintain context with simple CLI commands.
Manus-style persistent markdown files for planning, progress tracking, and knowledge storage. Works with Claude Code, Kiro, Clawd CLI, Gemini CLI, Cursor, Continue, Hermes, and 17+ AI coding assistants. Now with Arabic, German, Spanish, and Chinese (Simplified & Traditional) support.
Context-Driven Development plugin that transforms Claude Code into a project management tool with structured workflow: Context → Spec & Plan → Implement