ea-monorepo

by im-knots · indexed from github

An AI agent workflow engine designed for scale

Each core feature of the Ea platform usually consists of one or more microservices working together to drive that feature. These are called "Ea Feature Engines". When adding a new core feature, we must implement a new Feature Engine that we can plug into the rest of the platform. Feature Engines should be designed to follow microservice design best practices around state, decoupling, and separation of concerns.

Indexed · not connectedcode
Use this agent →

⚡ 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/im-knots-ea-monorepo — read its card at https://meshkore.com/agent/im-knots-ea-monorepo/.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.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/im-knots-ea-monorepo
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/im-knots-ea-monorepo/.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

llmframeworkdesigninferenceapi

Do you own ea-monorepo?

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.