{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/4"}],"enrichment":{"capability":"Builds hierarchical multi-agent systems where a supervisor agent coordinates and delegates tasks to specialized worker agents using LangGraph.","skillfed_tags":["multi-agent-systems","agent-orchestration","langgraph"],"use_cases":["Route customer support queries to specialized agents (billing, technical, account management) based on intent","Coordinate research and math agents to answer complex questions requiring both data lookup and calculation","Build multi-level hierarchies where team supervisors report to a top-level supervisor for large organizations","Manage conversation history and context across multiple specialized agents in a single workflow","Add persistent memory and human approval steps to multi-agent workflows via LangGraph checkpointers"],"what_it_does":"langgraph-supervisor provides a Python library for building hierarchical multi-agent systems on top of LangGraph. It implements a supervisor pattern where a central agent orchestrates communication and task delegation to specialized worker agents. The supervisor makes routing decisions based on context and task requirements, controlling all message flow between agents.\n\nThe library handles the mechanics of agent coordination\u2014tool-based handoffs, message history management, and multi-level hierarchies\u2014so you can focus on defining specialized agents and their supervisor's decision logic. It integrates with LangGraph's streaming, memory, and human-in-the-loop capabilities. However, the library's own documentation now recommends using the supervisor pattern directly via tool-calling for most use cases, suggesting this library is best suited for users upgrading existing code or cases where its abstraction provides clear value.","worth_installing":"Yes, if you are building a hierarchical multi-agent system and prefer a structured abstraction over manual tool-calling. The library is actively maintained, has low install friction, and integrates well with LangGraph's ecosystem. However, review the library's own recommendation to use tool-calling directly for most new projects\u2014install this primarily to upgrade existing code or when the supervisor abstraction clearly simplifies your architecture."},"id":"langgraph-supervisor","links":{"html":"https://skillfed.io/packages/langgraph-supervisor","md":"https://skillfed.io/packages/langgraph-supervisor.md","pypi":"https://pypi.org/project/langgraph-supervisor/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-11-19","license_spdx":"MIT","license_treatment":"permissive","name":"langgraph-supervisor","python_support":"supports_current","summary":"An implementation of a supervisor multi-agent architecture using LangGraph"},"popularity":{"monthly_downloads":718713,"position":5242,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.0.31"}