By eplord
LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.4
Build AI assistant application with NLU, dialog management, and integrations
Create LangGraph-based agent with modern patterns
Optimize prompts for production with CoT, few-shot, and constitutional AI patterns
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
Expert prompt engineer specializing in advanced prompting techniques, LLM optimization, and AI system design. Masters chain-of-thought, constitutional AI, and production prompt strategies. Use when building AI features, improving agent performance, or crafting system prompts.
Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similarity search. Use PROACTIVELY for vector search implementation, embedding optimization, or semantic retrieval systems.
Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.
Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.
Design LLM applications using LangChain 1.x and LangGraph for agents, memory, and tool integration. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
Uses power tools
Uses Bash, Write, or Edit tools
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⚡ Updated for Opus 4.7, Sonnet 4.6 & Haiku 4.5 — Three-tier model strategy for optimal performance
🎯 Agent Skills Enabled — 153 specialized skills extend Claude's capabilities across plugins with progressive disclosure
A comprehensive production-ready system combining 185 specialized AI agents, 16 multi-agent workflow orchestrators, 153 agent skills, and 100 commands organized into 80 focused, single-purpose plugins for Claude Code.
[!NOTE] Gemini CLI users: This ecosystem is also available as a native Gemini CLI extension — 153 skills discoverable on-demand, no plugin installation required. See GEMINI.md for setup.
This unified repository provides everything needed for intelligent automation and multi-agent orchestration across modern software development:
Each plugin is completely isolated with its own agents, commands, and skills:
Example: Installing python-development loads 3 Python agents, 1 scaffolding tool, and makes 16 skills available (~1000 tokens), not the entire marketplace.
Add this marketplace to Claude Code:
/plugin marketplace add wshobson/agents
This makes all 80 plugins available for installation, but does not load any agents or tools into your context.
Browse available plugins:
/plugin
Install the plugins you need:
# Essential development plugins
/plugin install python-development # Python with 16 specialized skills
/plugin install javascript-typescript # JS/TS with 4 specialized skills
/plugin install backend-development # Backend APIs with 3 architecture skills
# Infrastructure & operations
/plugin install kubernetes-operations # K8s with 4 deployment skills
/plugin install cloud-infrastructure # AWS/Azure/GCP with 4 cloud skills
# Security & quality
/plugin install security-scanning # SAST with security skill
/plugin install comprehensive-review # Multi-perspective code analysis
# Full-stack orchestration
/plugin install full-stack-orchestration # Multi-agent workflows
Each installed plugin loads only its specific agents, commands, and skills into Claude's context.
You install plugins, which bundle agents:
| Plugin | Agents |
|---|---|
comprehensive-review | architect-review, code-reviewer, security-auditor |
javascript-typescript | javascript-pro, typescript-pro |
python-development | python-pro, django-pro, fastapi-pro |
blockchain-web3 | blockchain-developer |
# ❌ Wrong - can't install agents directly
/plugin install typescript-pro
Kubernetes manifest generation, networking configuration, security policies, observability setup, GitOps workflows, and auto-scaling
CI/CD pipeline configuration, GitHub Actions/GitLab CI workflow setup, and automated deployment pipeline orchestration
Backend API design, GraphQL architecture, workflow orchestration with Temporal, and test-driven backend development
Distributed system tracing and debugging across microservices
Interactive debugging, developer experience optimization, and smart debugging workflows
npx claudepluginhub p/eplord-llm-application-dev-plugins-llm-application-devAccess thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Complete developer toolkit for Claude Code
Consult multiple AI coding agents (Gemini, OpenAI, Grok, Perplexity, plus codex and antigravity CLIs when installed) to get diverse perspectives on coding problems
Production-grade engineering skills for AI coding agents — covering the full software development lifecycle from spec to ship.
Intelligent draw.io diagramming plugin with AI-powered diagram generation, multi-platform embedding (GitHub, Confluence, Azure DevOps, Notion, Teams, Harness), conditional formatting, live data binding, and MCP server integration for programmatic diagram creation and management.
Orchestrate multi-agent teams for parallel code review, hypothesis-driven debugging, and coordinated feature development using Claude Code's Agent Teams