neumann-query

What problem does it solve?

This Skill helps developers and data engineers write syntactically correct and semantically valid Neumann database queries across relational, graph, vector, and unified engines, reducing errors, parser mis-tokenization, and wasted debugging time.

Core Features & Use Cases

• Common syntax gotchas: highlights direction keywords, colon-key tokenization, quoting rules for keys with colons, arrow and colon delimiters for edges, property block syntax, and SIMILAR metric/limit ordering.
• Cross-engine patterns: shows combined vector+graph queries, NEIGHBORS ranked by similarity, ENTITY workflows spanning relational/graph/vector, and when to use Vault/Cache/Blob commands.
• Authoritative references: maps commands to result types and points to parser and AST sources for precise behavior and validation.
• Use cases: RAG retrieval combining EMBED and graph traversal, agent memory with semantic caching, and structured entity creation with embeddings and graph links.

Quick Start

Write a Neumann query that finds engineers similar to 'user:alice' who report to 'user:bob'.