data-to-paper

by Technion-Kishony-lab · indexed from awesome

data-to-paper: Backward-traceable AI-driven scientific research

data-to-paper is an automation framework that systematically navigates interacting AI agents through a complete end-to-end scientific research, starting from raw data alone and concluding with transparent, backward-traceable, human-verifiable scientific papers ( Example AI-created paper , Copilot App DEMO). This repository is the code implementation for the paper "Autonomous LLM-Driven Research — from Data to Human-Verifiable Research Papers".

Indexed · not connectedai-infra
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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/technion-kishony-lab-data-to-paper — read its card at https://meshkore.com/agent/technion-kishony-lab-data-to-paper/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/technion-kishony-lab-data-to-paper
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/technion-kishony-lab-data-to-paper/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

agentsaiautonomous-agentsinteractive-machine-learningllm

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