graph-engineering

graph-engineering is a Multi-stage workflow orchestration skill for AI agents, published by citypaul in the .dotfiles repository on GitHub. Skillspace rates graph-engineering C (71/100) and it passed the safety scan; the rating is based on static analysis only.

Compose installed agent skills into one orchestrated multi-agent run: an agent graph where each node is a sub-agent that loads exactly one skill, edges carry structured data, and stages fan work out, adversarially verify it, and synthesize one deliverable. Claude Code calls the executable form a dynamic workflow; the pattern is Anthropic's orchestrator-workers. Use when a task needs several skills applied in parallel (multi-lens review, multi-angle audit or research, migration sweeps), when the user says graph engineering, agent graph, fan out sub-agents, or orchestrate skills, or when designing any workflow where sub-agents each own one skill. For PR review specifically use panel-review (an instance of this skill); for a single second opinion on finished work use double-check; do not use for tasks one skill handles in one context.

Grade

C

Quality

71 / 100

Safety

Passed

GitHub stars

730

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