claude-to-deerflow

To send messages to the DeerFlow AI agent, you use the claude-to-deerflow skill to interact with its HTTP API endpoints. This enables sending questions or prompts directly to DeerFlow for research and analysis.

Yes, you can delegate complex research tasks to DeerFlow from your local environment. The skill enables task delegation to the DeerFlow AI agent platform, which handles extensive analysis requiring multiple sub-agents.

To manage DeerFlow conversations and memory via HTTP API, you need a running DeerFlow instance and an understanding of its HTTP API endpoints. The skill allows you to start conversation threads and manage memory.

Yes, the DeerFlow API supports file uploads to conversation threads. You can use the skill to upload files directly to active threads, enabling the AI agent to process and analyze the provided documents.

You can check DeerFlow agent status and list available models by interacting with the platform's HTTP API. The skill provides functionality to query conversation status and retrieve the list of models supported by the DeerFlow instance.

The primary limitation of using the HTTP API for DeerFlow conversation management is the strict dependency on having a running DeerFlow instance. You must also understand its specific HTTP API endpoints to successfully send messages and manage memory.