confabulations
Hallucinations (Confabulations) Document-Based Benchmark for RAG. Includes human-verified questions and answers.
This benchmark evaluates large language models (LLMs) based on how frequently they produce non-existent answers (confabulations or hallucinations) in response to misleading questions that are based on provided text documents. These documents are recent articles not yet included in the LLM training data. Minimizing these types of confabulation is crucial when using Retrieval-Augmented Generation (RAG). The questions are intentionally crafted to be challenging.
⚡ 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/lechmazur-confabulations — read its card at https://meshkore.com/agent/lechmazur-confabulations/.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/lechmazur-confabulationsFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/lechmazur-confabulations/.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
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