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ai-ml-engineering-pack

Professional AI/ML Engineering toolkit: Prompt engineering, LLM integration, RAG systems, AI safety with 12 expert plugins

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AuthorJeremy Longshore
Namespace@jeremylongshore/claude-code-plugins-plus
Category#ai-ml
Version1.0.0
Stars★ 1,193
Downloads↓ 10
Verification[ ✓ ] self.md verified

Professional AI/ML Engineering toolkit: Prompt engineering, LLM integration, RAG systems, AI safety with 12 expert plugins

Installation

npx claude-plugins install @jeremylongshore/claude-code-plugins-plus/ai-ml-engineering-pack

Contents

Folders: docs, plugins, skills

Files: LICENSE, README.md

Documentation

Professional toolkit for building production-ready AI/ML systems with Claude Code

Master prompt engineering, LLM integration, RAG systems, and AI safety with 12 specialized plugins that accelerate AI development by 10x.

License: MIT Version Claude Code

What’s Included

12 specialized plugins across 4 AI/ML categories:

1. Prompt Engineering (3 plugins)

  • prompt-architect (agent) - Expert in CoT reasoning, few-shot learning, and advanced prompt patterns
  • prompt-optimizer (agent) - Reduce LLM costs by 60-90% while maintaining quality
  • prompt-template-gen (command: /ptg) - Generate production-ready prompt templates with type safety

2. LLM Integration (3 plugins)

  • llm-integration-expert (agent) - Production API patterns, error handling, streaming, rate limiting
  • model-selector (agent) - Choose optimal models based on cost, quality, latency requirements
  • llm-api-scaffold (command: /las) - Generate complete LLM API with FastAPI, Docker, monitoring

3. RAG Systems (3 plugins)

  • rag-architect (agent) - Design RAG systems, chunking strategies, retrieval optimization
  • vector-db-expert (agent) - Select and configure vector databases (Pinecone, Qdrant, Weaviate, etc.)
  • rag-pipeline-gen (command: /rpg) - Generate complete RAG pipeline with embeddings and retrieval

4. AI Safety (3 plugins)

  • ai-safety-expert (agent) - Content filtering, PII detection, bias mitigation, compliance
  • prompt-injection-defender (agent) - Defend against prompt injection and jailbreak attacks
  • ai-monitoring-setup (command: /ams) - Set up LLM monitoring, cost tracking, and alerts

Quick Start

Installation

# Add the marketplace (if not already added)
claude plugin marketplace add jeremylongshore/claude-code-plugins

# Install AI/ML Engineering Pack
claude plugin install ai-ml-engineering-pack@claude-code-plugins-plus

# Verify installation
claude plugin list

Full installation guide: INSTALLATION.md

10-Minute Tutorial

Build your first AI feature in 10 minutes:

# Start Claude Code
claude

# Inside Claude, optimize a prompt
"Optimize this prompt for cost and quality:
'I would like you to create a detailed product description for...'"
# Claude uses prompt-optimizer agent to reduce tokens by 70%

# Generate a reusable prompt template
/ptg

# Build a production LLM API
/las

# Create a complete RAG system
/rpg

# Add AI safety guardrails
"Implement PII detection and toxicity filtering for my chatbot"

Complete tutorial: QUICK_START.md

ROI & Value Proposition

Real-world results from production deployments:

Use CaseTime SavedCost SavingsROI
E-Commerce Recommendations12.5 hours$249,250/year11,891%
Legal Document Analysis12 hours$781,500/year34,192%
Customer Support Automation16 hours$350,400/year11,283%
Content Moderation19 hours$1,872,000/year40,781%
Code Documentation145 hours$14,100 (one-time)2,565%
Medical Diagnosis Assistant28 hours$44,600,000/year75,392%

Average ROI: 29,351% | Average payback period: 3 days

Detailed case studies: USE_CASES.md

Plugin Reference

Prompt Engineering

prompt-architect (Agent)

Expert in advanced prompt engineering techniques and patterns.

Capabilities:

  • Chain-of-Thought (CoT) reasoning
  • Few-shot and zero-shot learning
  • Prompt composition patterns
  • Meta-prompting and self-improvement
  • Multi-modal prompts (text + images)

When to use:

  • “Design a prompt for [complex task]”
  • “Improve this prompt: [existing prompt]”
  • “What’s the best prompting technique for [use case]?”

Activation triggers: Prompt design, CoT, few-shot learning, prompt patterns


prompt-optimizer (Agent)

Optimize prompts for cost reduction (60-90% savings) while maintaining quality.

Capabilities:

  • Token reduction techniques (remove verbosity, use abbreviations)
  • Prompt caching strategies
  • Model selection guidance (cheap vs expensive)
  • Cost-quality trade-off analysis
  • ROI calculation

When to use:

  • “Reduce the cost of this prompt: [prompt]”
  • “Optimize my prompts for $1000/month budget”
  • “How can I reduce token usage by 70%?”

Example:

Before (52 tokens): "I would like you to please analyze..."
After (15 tokens): "Analyze and summarize main points."
Savings: 71% token reduction = $0.15/1000 calls (GPT-4)

Activation triggers: Cost optimization, token reduction, prompt efficiency


/ptg - Prompt Template Generator (Comman

Included Skills

This plugin includes 1 skill definition:

optimizing-prompts

|

View skill definition

Ai Ml Engineering Pack

This skill provides automated assistance for ai ml engineering pack tasks.

Overview

This skill provides automated assistance for ai ml engineering pack tasks. This skill empowers Claude to refine prompts for optimal LLM performance. It streamlines prompts to minimize token count, thereby reducing costs and enhancing response speed, all while maintaining or improving output quality.

How It Works

  1. Analyzing Prompt: The skill analyzes the input prompt to identify areas of redundancy, verbosity, and potential for simplification.
  2. Rewriting Prompt: It rewrites the prompt using techniques like concise language, targeted instructions, and efficient phrasing.
  3. Suggesting Alternatives: The skill provides the optimized prompt along with an explanation of the changes made and their expected impact.

When to Use This Skill

This skill activates when you need to:

  • Reduce the cost of using an LLM.
  • Improve the speed of LLM responses.
  • Enhance the quality or clarity of LLM outputs by refining the prompt.

Examples

Example 1: Reducing LLM Costs

User request: “Optimize this prompt for cost and quality: ‘I would like you to create a detailed product description for a new ergonomic office chair, highlighting its features, benefits, and target audience, and also include information about its warranty and return policy.’”

The skill will:

  1. Analyze the prompt for redundancies and areas for simplification.
  2. Rewrite the prompt

Source

View on GitHub