12 AI tools for LangChain ?
Skill for RAG systems - semantic chunking, hybrid retrieval, advanced retrieval techniques, evaluation, and production.
Seven-phase bundle orchestrating specialist skills across LLM integration, RAG, agents, ML pipelines, observability, and AI security.
Guides using GigaChat through LangChain abstractions - chat models, embeddings, tool binding, and RAG - instead of the raw gigachat SDK.
A routing skill that picks the right GigaChat integration layer - native SDK, langchain-gigachat, or gpt2giga - for a given task.
Reliability-first patterns for autonomous AI agents - ReAct, Plan-Execute, Reflection loops, guardrails, and LangGraph checkpointing - plus failure modes.
Skill documenting LLM context-window strategies: tiered routing, serial-position optimization, importance-based summarization, and token budgets.
Langfuse LLM observability expert: tracing, prompt versioning, LLM-as-judge evaluation, datasets, and OpenAI/LangChain integration.
Provides patterns and checklists for building LangChain 0.1+ and LangGraph agents with Claude Sonnet 4.5, Voyage AI embeddings, async patterns, and LangSmith
Skill documenting tiered LLM conversation memory (buffer, short-term, long-term, entity) plus three common memory-system failure modes.
Archestra is an open-source enterprise AI platform combining an LLM gateway, MCP gateway, agent runtime, and RBAC/SSO governance.
Run your own MCP server on Azure Functions to connect AI agents to real-world APIs. Supports C#, Python, and TypeScript.
