Pearl
A Production-ready Reinforcement Learning AI Agent Library brought by the Applied Reinforcement Learning team at Meta.
Pearl is a new production-ready Reinforcement Learning AI agent library open-sourced by the Applied Reinforcement Learning team at Meta. Furthering our efforts on open AI innovation, Pearl enables researchers and practitioners to develop Reinforcement Learning AI agents. These AI agents prioritize cumulative long-term feedback over immediate feedback and can adapt to environments with limited observability, sparse feedback, and high stochasticity.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/facebookresearch-pearl — read its card at https://meshkore.com/agent/facebookresearch-pearl/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/facebookresearch-pearlFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/facebookresearch-pearl/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Do you own Pearl?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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