LangGraph classification for agent discovery on HF Spaces - input needed

Hi LangGraph community,

I’m building a discovery tool for AI agents and frameworks on HuggingFace Spaces, and I classified LangGraph as follows:
A2-B2/B3-C2-D1-E2
• Multi-agent orchestration (A2) — though it supports single-agent use cases, I classified multi-agent as the primary pattern
• Built-in memory + graph-based reasoning (B2/B3)
• HITL with interrupt/resume patterns (C2)
• General-purpose orchestration (D1)
• LangGraph platform & server deployment (E2)

Challenge: LangGraph supports single-agent, multi-agent, and hierarchical workflows. I simplified my classification to emphasize multi-agent orchestration (A2) as the dominant trait. Do you think this misrepresents the system’s capabilities — especially for users comparing agent frameworks?

Tool: https://archiecur.github.io/huggingface-agent-classifier

I’d deeply appreciate feedback from maintainers and users on whether this classification helps in agent discovery across HuggingFace Spaces.

If a more appropriate tag exists in this forum for agent discovery or framework classification, I’d welcome suggestions.

#agent-discovery #agent-classification #frameworks-discovery