exa-grounding

To ground an AI agent in domain-specific knowledge, this Skill uses Exa's neural search to perform deep research and synthesizes the findings into a clean knowledge core. This ensures the agent operates with expert-level understanding before executing tasks.

Knowledge grounding for AI agents is the process of bootstrapping the model with authoritative, domain-specific information before task execution. You need it when creating specialized agents, such as one for medical research grounded in peer-reviewed journals and clinical trial data.

Yes, you can use Supabase pgvector for persistent AI agent memory. The Skill optionally vectorizes the synthesized knowledge core and pushes it to Supabase, creating a searchable and persistent memory store for the agent.

You need an Exa API key to perform the neural search research, and Supabase connection details for the optional vector memory integration. The knowledge core synthesis itself relies primarily on the Exa search results.

The best way to bootstrap a medical research AI agent is using neural search to find authoritative content and distilling it into a knowledge core. This Skill leverages Exa search to gather peer-reviewed data and optionally stores it in Supabase pgvector.