ragret
Lightweight evaluation framework for Retrieval Augmented Generation systems, focused on simplicity and long-term consistency.
ragret is a lightweight, stable evaluation framework for Retrieval-Augmented Generation (RAG) systems that is designed for long-term consistency and only the necessary structural updates in mind. Its goal is simplicity: small, modular metrics that are easy to understand, extend, and integrate into existing pipelines. It was created out of the frustration with other frameworks constantly changing, making code from one version to the next obsolete and difficult to migrate.
⚡ 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/christopher-kormpos-ragret — read its card at https://meshkore.com/agent/christopher-kormpos-ragret/.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/christopher-kormpos-ragretFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/christopher-kormpos-ragret/.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 ragret?
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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