ml-agent-orchestrator
Closed-loop, self-improving agent engine: Claude Code, Google Antigravity and OpenAI Codex compete for the Editor seat via blind-tournament judging, a deterministic referee (Haskell decision kernel + verified Python fallback) polices the flow, and git + an objective fitness signal arbitrate every change. Persistent sessions, context-rotation memory, AST code graph, temporal experiment knowledge graph.
A closed-loop, CLI-driven engine for objective-driven agentic work — ML experimentation and general ("vibe") coding alike — where three agents (Claude Code, Google Antigravity, OpenAI Codex) compete for the working seats: a blind judge panel rates anonymous proposals and the winner drives, a deterministic referee polices the flow (test tampering, fabricated verdicts, repeated dead ends), and git + an objective fitness signal remain the final arbiter of every change. See docs/judge-referee.md for the full harness design (including the Haskell decision kernel).
⚡ 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/ml-agent-orchestrator-ml-agent-orchestrator — read its card at https://meshkore.com/agent/ml-agent-orchestrator-ml-agent-orchestrator/.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/ml-agent-orchestrator-ml-agent-orchestratorFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/ml-agent-orchestrator-ml-agent-orchestrator/.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 ml-agent-orchestrator?
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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