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Model the graph: decide whether you need one, design the ontology, and make traversal and graph retrieval perform.
Complete skill package instant downloadlucrezia-knowledge-graph-engineer.md
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Ask Lucrezia something hard.
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Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com
// the file itself
The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.
You are Lucrezia, a Senior Knowledge Graph Engineer who scores each use case before choosing between a property graph in Neo4j and RDF with SPARQL. You have been activated to model a domain and ground answers through GraphRAG.
// what's inside
Teams considering a knowledge graph who need a straight answer on whether it will pay for itself.
// two ways to get it
$7 one payment, yours forever
$9/mo cancel anytime, or $59 a year
Subscribers can still buy single files and keep them after they cancel.
// ask your assistant
Go to kissmyskills.com/pages/for-ai-agents and set up the "Lucrezia - Knowledge Graph Engineer AI Skill" skill (handle: lucrezia-knowledge-graph-engineer) for me
Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →
Drop Lucrezia into Claude and get a graph engineer who will tell you when your problem is a join, not a graph, before you buy a graph database.
Lucrezia works with data as a graph: when a graph genuinely beats relational and when it plainly does not; property graphs with Neo4j and Cypher versus RDF and SPARQL and the real tradeoff; ontology and taxonomy design, entity and relationship modelling and reification; entity resolution and disambiguation inside a graph; ingestion pipelines and incremental updates; graph algorithms in practice across pathfinding, centrality, community detection and similarity, and what each is actually good for; query performance, supernodes and index-free adjacency; graph embeddings and GNNs at a practical level; retrieval over graphs to ground LLM answers; and visualization a non-engineer can read.
What you get
How to install
Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Lucrezia builds the answer. Includes a full worked example so you see exactly what you get.
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
Claude, ChatGPT, Gemini, Grok, or Copilot - whichever one you already use.
Drop it into the system prompt, Project instructions, or custom instructions field.
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required.
With Unlimited there is nothing to download. Connect your AI once, then just ask: "Load Lucrezia from KissMySkills."
Model the graph: decide whether you need one, design the ontology, and make traversal and graph retrieval perform. Load it once into Claude Projects and you get a configured Knowledge Graph & Graph Data Engineer without re-explaining context at the start of every session. Check every number against a known-good source and an honest holdout before anyone builds a decision on it, and state the uncertainty instead of shipping a single confident point estimate.
Download the .skill package (it contains SKILL.md), paste the contents into Claude Projects Instructions or your AI's system prompt, add your own context and start your first session. Works with Claude, ChatGPT, or any AI chat that accepts system prompts.
Works with Claude (recommended), ChatGPT, Gemini, Perplexity and Copilot, and any AI chat that accepts system prompts. Claude Projects gives the best results.
Without a skill file your AI starts every session as a general assistant. With Lucrezia loaded it applies Knowledge Graph & Graph Data Engineer methodology from the first message, with consistent quality every time. Check every number against a known-good source and an honest holdout before anyone builds a decision on it, and state the uncertainty instead of shipping a single confident point estimate.