superagentic-metaharness
Unofficial implementation of the Meta Harness paper for coding-agent harness optimization.
metaharness is an open source Python library for optimizing executable harnesses around agentic coding systems. It is inspired by the Meta Harness paper and is an unofficial open source implementation of the core ideas in that work. The current benchmark evidence in this repository is centered on the Codex CLI path, including hosted Codex and Codex over local Ollama models. Codex is the primary and validated backend in this repository today. Gemini CLI and Omnigent are additional experimental integrations.
⚡ 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/superagentic-ai-superagentic-metaharness — read its card at https://meshkore.com/agent/superagentic-ai-superagentic-metaharness/.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/superagentic-ai-superagentic-metaharnessFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/superagentic-ai-superagentic-metaharness/.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 superagentic-metaharness?
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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