graph-engineering

The context orchestration layer powered by hypergraphs. Build a unified semantic context layer where agentic outcomes are deterministic and agent behavior is not just traceable, but cryptographically verifiable.

An open-source graph engineering runtime that keeps orchestration in TypeScript and delegates semantic work to replaceable Agent runtimes.

A Survey on Ontology Engineering, Graph Engineering, Loop Engineering, Harness Engineering, Context Engineering and Prompt Engineering

[Up-to-date] A curated list of resources on graph-empowered agents and agent-facilitated graph learning (Graphs Meet Agents & Agentic Graph Engineering).

A context graph which is based on confidence-aware belief that drives more determinstic reasoning in long-horizon agents.

agent wiki +engineering skills

The structured context layer for AI agents. Build self-learning specialised agents that are context aware.

Build stateful agent workflows with typed outputs, reusable tools, session forks, and ordinary TypeScript.

Personal-memory-driven AI work twin that uses Codex to work inside real projects.

Turns repeatable, domain-agnostic workflows into graph-driven loops.

🦦 ADHDev — Agent Dashboard Hub. Monitor & control AI coding agents from a single dashboard. Self-hosted, open-source.

Desktop app for harness engineering, loop engineering, graph engineering—and whatever comes next in local AI-agent workflows.

Graph Engineering, simplified — with GraphCode. #graphcode

Long-horizon agent skill for Claude Code / Cursor / Codex / Grok Build — multi-task ledger loop, host-portable, clean-context supervisor, verified gates. Markdown library (loop-graph), not a framework.

An end to end implementation of Graph Engineering as proposed by Andrew NG and Peter Steinberger

🕸️ Engineer the organization, not just the agent. 565 curated resources · 9 design layers · 11 sections · 255 papers & preprints — a field guide, CC0 open dataset, and interactive atlas for graph-structured multi-agent systems: roles, topologies, handoffs, work graphs, state, gates, reliability, observability.

A graph-engineering agent harness for long-horizon, research-level autoformalization.

This repository serves as the comprehensive workspace for Quarter 4-5 academic endeavors, encompassing assignments, technical documentation, experimental implementations, and applied projects.

A playbook framework for Claude Code and the sprint loop built on it — deterministic state machinery, model-driven steps, plain-markdown vault

Graph Engineering for Agent Skills: a specification and toolchain for dynamically discovering context and building observable, testable, and recoverable agent workflows.