graph-engineering

The deterministic context engineering platform for open source AI. Connect open models and ontologies with context graph harnesses to build explainable, reliable agents.

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

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

agent wiki +engineering skills

AI Agent Skills, Loops and Dynamic Workflows for Security Auditing, Pentesting and Research

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

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

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

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

🕸️ Engineer the organization, not just the agent. 562 curated resources · 9 design layers · 11 sections · 252 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.

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

Copy-paste prompts that turn your AI agents from a waiting line into a graph: a 5-min demo, false-edge audit, diamond research, adversarial review, consultant roundtable, and an issue tree that dispatches itself. EN + 繁中.

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

DyroEngineeringFlow 是面向多仓团队的本地优先工程自动化与交付控制平台。它将开发线、Git worktree、任务编排、 Agent 启动、质量门禁、独立复核与合并审计统一到可版本化配置中，帮助团队从任务创建到交付合并形成清晰、安全、 可追溯的自动化流程。日常通过简洁命令 dyro 即可完成初始化、环境检查、任务执行与协作交付。

Installable graph engineering for Claude Code, Codex, OpenCode, Cursor, and OpenClaw — dependency-graph execution with local caching, quality gates, selective retries, and live reports

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

Design grounded graphs of governed improvement loops.

A production-grade Python & Streamlit reference implementation of the 5-Layer Graph Engineering Taxonomy, implementing the complete technical outline

Vendor-neutral graph orchestration for reliable agentic systems: one portable Graph IR, native TypeScript/Python runtimes, deterministic barriers/routers, and cross-language conformance.