RedDebate
Multi-agent debate framework for enhancing LLM safety through red-teaming prompts, feedback-driven learning, long-term memory, and diverse structured debate strategies.
RedDebate is a fully automated framework that lets a pool of Large Language Models red-team each other through debate. Rather than treating a model's reply as a final answer, RedDebate frames it as a claim to be tested, challenged, and iteratively refined by other agents. An independent evaluator flags unsafe behaviour, a feedback agent distils the incident into a safety lesson, and long-term memory carries those lessons into every future debate — so the system keeps improving itself without any human in the loop.
⚡ 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/aliasad059-reddebate — read its card at https://meshkore.com/agent/aliasad059-reddebate/.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/aliasad059-reddebateFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/aliasad059-reddebate/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own RedDebate?
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.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.