graph-engineering vs loop-engineering
Graph engineering as a Claude skill: SEU's 9-stage knowledge-graph course (translated) plus task-graph orchestration patterns — with a teaching mode and nine paste-ready /kg workflows. — versus — Reference repo plus npm CLIs (loop-init/audit/cost) for loop engineering: designing scheduled, gated control loops that prompt and orchestrate AI coding agents — Grok, Claude Code, Codex — over time.
Sibling discipline-defining repos — loop engineering steers an agent's iterations through gated control loops; graph engineering steers its topology. The repo's own lineage sentence places them side by side. Read both, adopt the layer you're missing.
| graph-engineering | loop-engineering | |
|---|---|---|
| Stars | 144 | 9.5k |
| Forks | 19 | 1.3k |
| Language | — | JavaScript |
| License | MIT | MIT |
| Last activity | 4 days ago | today |
| Topics | skills | coding, orchestration |
| Curated connections | 3 | 9 |
graph-engineering — the curator's take
A discipline-in-a-repo: the thesis that agents are steered by topology — knowledge graphs for what they remember, task graphs for how they work — backed by an actual graduate curriculum (SEU's 4.4k-star course, translated from Chinese) rather than vibes. The teaching mode is the standout: /kg-tutor walks the whole pipeline drawing diagrams from YOUR domain, and eight chained workflows go from scoping to GraphRAG. NOT proven at scale: 144 stars and young — adopt it as excellent structured knowledge, not battle-tested tooling; the graphs you build with it still need the engineering the course itself teaches (fusion and provenance are where naive KG projects drown).
loop-engineering — the curator's take
The methodology layer for autonomous coding agents — read it once you've stopped hand-prompting and want to design the loop that prompts the agent instead: scheduled triage, worktree isolation, maker/checker sub-agents, MCP connectors, human gates, and a phased L1-report → L3-unattended rollout. Ships 7 clone-and-run patterns, tool-agnostic starters (Grok/Claude Code/Codex/OpenCode), and CLIs that score loop-readiness (loop-audit), estimate token spend (loop-cost) and scaffold state/budget (loop-init). It's a patterns + tooling reference, NOT a runtime — it won't execute or host your agents, so bring your own harness (an alook-style AI-company layer or a squid-style pipeline). Overkill if you just want one-shot interactive help; heed its own caveat that unattended loops make unattended mistakes, so verification stays on you.