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By laurigates
Build and develop LangChain LLM applications in TypeScript/JavaScript and Python: initialize projects with Bun/NPM and core deps, create chains/agents/RAG with OpenAI/Anthropic/Zod, construct stateful LangGraph workflows with checkpoints/human-in-loop, and assemble hierarchical deep agents for multi-step orchestration, file context, subagents, and persistent memory.
npx claudepluginhub laurigates/claude-plugins --plugin langchain-pluginBuild hierarchical AI agents using the deep-agents TypeScript/npm package. Use when you want to create an orchestrator agent that plans and executes multi-step tasks, manages file system context, delegates subtasks to child agents, or maintains persistent memory across runs with the Deep Agents library.
LangChain JS/TS framework for building LLM-powered applications - models, chains, tools, and RAG patterns.
Initialize a new LangChain TypeScript project with recommended configuration
Build stateful AI agents in Python using LangGraph's graph-based workflow framework. Use when you want to create a state machine agent with checkpoints, define agent behavior as a graph of nodes and edges, add human-in-the-loop approval steps, or compose multiple agents as subgraphs in a LangGraph application.
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Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Prompt engineering techniques for accurate, grounded Claude responses — anti-hallucination workflow with citation-backed analysis
Language-agnostic development process harness implementing the Stateless Agent Methodology (SAM) 7-stage pipeline with ARL human touchpoint model and Voltron-style language plugin composition. Provides orchestration, workflows, planning, verification, and testing methodology that any language plugin can compose with.
Complete collection of battle-tested Claude Code configs from an Anthropic hackathon winner - agents, skills, hooks, and rules evolved over 10+ months of intensive daily use
LLM application development with RAG, embeddings, LangChain, and prompt engineering
Unified capability management center for Skills, Agents, and Commands.
Expert agents for specific programming languages (Python, Go, Rust, etc.)
Rust development - cargo, clippy, testing, memory safety
Bevy game engine development - ECS, rendering, game architecture
Test execution, TDD workflow, testing strategies, and quality analysis
Python development ecosystem - uv, ruff, pytest, packaging, type checking
Home Assistant configuration management - YAML configuration, automations, scripts, scenes, and entity management for Home Assistant installations
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