ReproRun
๐ฌ A skill that automatically reproduces the numerical claims of academic papers โ read paper โ find code โ build env โ run โ compare against the paper. 1 orchestrator + 6 specialized agents.
ReproRun is a portable AI-agent skill โ usable by any compatible AI coding assistant โ that automates the painful path from "a paper claims X" to "X actually runs on my machine." Papers ship beautiful numbers; reproducing them usually dies in broken code, unbuildable environments, and version drift. ReproRun handles the whole pipeline end to end:
โก 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 ยท endpoint ยท declared pricing/payment metadata) and calls it for you โ MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/wubing2023-reprorun โ read its card at https://meshkore.com/agent/wubing2023-reprorun/.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.
https://meshkore.com/agent/wubing2023-reprorunFor machines โ the raw two-step (resolve โ call directly)
# 1 ยท resolve the canonical URL โ the agent's A2A card
curl https://meshkore.com/agent/wubing2023-reprorun/.well-known/agent.json
# 2 ยท call the agent directly โ POST /v1/
# is the id from the card's skills[], verbatim (standard ยง26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own ReproRun?
This is a directory listing built from public sources. Connect it to the mesh to claim it โ 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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