Root1V

Aeon Agent Harness

AI community

SOURCE https://github.com/Root1V/aeon-agent-harness

Description

Self-hosted agent harness platform: durable Temporal execution, typed context/evidence, policy enforcement outside the model, governed memory, and native interop with LangGraph, CrewAI, OpenAI Agents SDK, Microsoft Agent Framework, and Claude Agent SDK.

Installation

This entry records only its repository, not the path inside it, so there is no exact command to give. Open the source below and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

README

Aeon — Agent Harness Platform

Aeon is a self-hosted, container-first platform that gives an AI agent project the infrastructure it always needs and always reimplements badly: a durable execution loop, typed context management, verifiable evidence and citations, authorization enforced outside the model, hard budgets, OTel tracing, and eval gates — without locking you into one model provider or one agent framework.

**Status:** early scaffolding. See [roadmap.md](roadmap.md) for what's actually done (with a passing acceptance test) vs. stubbed vs. not started. Don't trust a feature is real until its row says `DONE` — that status is mechanically checked, see `make roadmap-check`.

Why

The thesis (see the original spec this project is built from, `Especificacion_Arnes_Agentico_AI_2026.md`, and the architecture decisions in [docs/adr/](docs/adr/)): **the harness, not the model, determines whether an agent survives production.** Aeon is that harness, built once, reused across projects.

Architecture at a glance

Control plane (Go): Agent/Tool/Prompt/Skill/Eval/Policy registries, Cedar-based authorization, approvals, ABOM.
Model Gateway (Go): the only component allowed to talk to a model provider directly. Adapters for anthropic, openai, gemini, prometheus_inference (local inference), and a generic openai_compatible fallback — behind one Provider interface (docs/adr/0004). An AgentManifest names a capability profile, never a concrete model.
Tool Gateway (Go): typed tool schemas, risk classification, policy check after arguments are generated and before execution, idempotent execution with a dedupe table, MCP client/server.
Agent Workers (Python, on Temporal): the deterministic workflow/non-deterministic activity split that makes crash-and-resume safe — see docs/adr/0001. This is proven, not aspira