ACE_Model_Implementation
A python implementation of Dave Shap's ACE Model
The aim is to create a python implementation of the Autonomous Cognitive Entity (ACE) model that is modular in nature so that LLMs / resources / capabilities can be swapped in and out. A modular design should also make it is easier for the program to implement polymorphic features, and also easier to be slotted into various forms of deployment and UI depending on the use case.
⚡ 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/ckemplen-acemodelimplementation — read its card at https://meshkore.com/agent/ckemplen-acemodelimplementation/.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/ckemplen-acemodelimplementationFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/ckemplen-acemodelimplementation/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Do you own ACE_Model_Implementation?
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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