Ingest graph-queue JSON into Neo4j with idempotent MERGE-based insertion.
npx skills add https://github.com/YH-05/quants --skill save-to-graph
Please help me install this Agent Skill. Skill: save-to-graph Source: https://github.com/YH-05/quants/tree/main/.claude/skills/save-to-graph Command: npx skills add https://github.com/YH-05/quants --skill save-to-graph
Ingest graph-queue JSON into Neo4j, performing idempotent MERGE-based insertion of nodes and relationships to build a consistent knowledge graph according to KG v2.2.
Load a graph-queue JSON file and execute the four-phase pipeline to merge nodes and relationships into Neo4j.
High-intent search queries and answers about installing and using this skill.
Idempotent MERGE-based insertion loads JSON data into Neo4j without creating duplicate nodes. By using deterministic IDs, repeated pipeline runs update existing graph entries instead of appending duplicates, ensuring a consistent knowledge graph.
Building a knowledge graph from a JSON queue involves a four-phase pipeline: queue detection, node insertion, relationship insertion, and completion handling. This process merges 14 node types and 31 relationships according to the KG v2.2 schema.
Idempotent ETL pipeline ingestion supports schema validation for Neo4j. It validates graph-queue JSON against the KG v2.2 schema, ensuring 14 node types and 31 relationships are correctly structured before performing any merge operations.
Robust error handling manages connectivity and queue integrity errors during graph data ingestion. The pipeline detects queue issues and validates data formats before insertion, preventing incomplete JSON loads from corrupting the Neo4j knowledge graph.
You can use MERGE operations to update an existing Neo4j knowledge graph with new JSON data. The pipeline applies idempotent merges using deterministic IDs, ensuring re-running the JSON queue updates existing nodes and relationships without duplication.
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