graph-engineering

Compose installed agent skills into orchestrated multi-agent graphs with adversarial verification.

723|93|Updated Nov 14, 2021
One-click install
npx skills add https://github.com/citypaul/.dotfiles --skill graph-engineering
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: graph-engineering
Source: https://github.com/citypaul/.dotfiles/tree/main/claude/.claude/skills/graph-engineering
Command: npx skills add https://github.com/citypaul/.dotfiles --skill graph-engineering

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Applying multiple review or analysis skills to one task in a single context produces shallow, overlapping results with no independent verification. This Skill turns a library of installed skills into a coordinated multi-agent graph where each sub-agent node loads exactly one skill, works a bounded scope, and returns schema-shaped findings that are deduplicated, adversarially verified, and synthesized into one deliverable.

Core Features & Use Cases

  • Skills-as-nodes orchestration: Map responsibilities to installed skills one per node, fan them out in parallel, and keep each lens isolated in its own context.
  • Structured contracts and verification: Every stage returns schema-shaped findings with file:line evidence and fixed severities; independent verifier nodes attempt to refute each finding before it is reported.
  • Three runtimes: Prefer the Workflow tool (dynamic workflows with enforced schemas and resume), fall back to Agent-tool fan-out, or run a labeled sequential degraded mode.
  • Use Case: Reviewing a large pull request through five architectural lenses at once — scout the diff inline, fan out one node per skill, dedup findings, verify each adversarially, and deliver a severity-ranked report stating what was covered and what was not.

Quick Start

Ask the agent to use graph engineering to fan out one sub-agent per relevant skill over this change set, verify the findings adversarially, and synthesize a single ranked report.

Frequently Asked Questions about graph-engineering

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run multiple agent skills in parallel on one task?▼

Design an agent graph: scout the scope inline, assign one installed skill per sub-agent node with a bounded scope, and fan the nodes out concurrently. Each node returns schema-shaped findings that are deduplicated, verified, and synthesized into one deliverable.

What is the orchestrator-workers pattern for AI agents?▼

Orchestrator-workers is a pattern where one orchestrator decomposes a task, dispatches sub-agents (workers) with isolated contexts, and synthesizes their results. In Claude Code its executable form is a dynamic workflow built with the Workflow tool's agent, parallel, pipeline, and phase primitives.

When should I not use a multi-agent graph?▼

Skip the graph when one skill in one context handles the task, when steps need each other's full context sequentially, or when the user has not opted into multi-agent cost. A graph amplifies a clear question but cannot rescue a vague one.

How does adversarial verification work in an agent graph?▼

Each surviving finding is sent to an independent verifier node instructed to refute it against the actual code. Verdicts are confirmed, refuted, or unverifiable; unverifiable claims are reported rather than silently dropped or kept.

Can sub-agents load skills without the Skill tool?▼

Yes. On hosts without a Skill tool, nodes fall back to reading the skill file directly from the project's .claude/skills directory or the user's ~/.claude/skills directory, with the resolved path passed in the node brief.

What happens if a node fails during a graph run?▼

Failed nodes resolve to null and are filtered out, with the failure count reported in the final deliverable. If most of a roster fails the same way, the brief is broken and should be fixed before rerunning only the failed nodes.