Individual skill
modeling-nosql-data
Build use when you need to work with NoSQL data modeling. This skill provides NoSQL database design with comprehensive guidance and automation. Trigger with phrases like "model NoSQL data", "design document structure", or "optimize NoSQL schema".
skills/.curated/modeling-nosql-data/SKILL.md
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- Repository last updated
- Nov 12, 2026
- License
- MIT
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- ai Repository topic
- automation Repository topic
- claude-code Repository topic
- devops Repository topic
- mcp Repository topic
- ai-agents Repository topic
- anthropic Repository topic
- claude-code-plugins Repository topic
- developer-tools Repository topic
- llm Repository topic
- database Declared skill tag
- modeling-nosql Declared skill tag
- data Derived category
- data-databases Derived category
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SKILL.mdcore · 6,785 bytesSKILL.mdcore · 6,785 bytesassets/README.mddoc · 320 bytesreferences/README.mddoc · 61 bytesscripts/README.mddoc · 367 bytesscripts/generate_sample_data.pyruns · 11,358 bytesscripts/migrate_schema.pyruns · 13,633 bytesscripts/validate_schema.pyruns · 15,808 bytes
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# NoSQL Data Modeler
## Overview
Design data models for NoSQL databases including MongoDB (document), DynamoDB (key-value/wide-column), Redis (key-value), and Cassandra (wide-column). Unlike relational modeling where normalization drives design, NoSQL modeling starts from access patterns and query requirements, then shapes the data to serve those patterns efficiently.
## Prerequisites
- `mongosh`, `aws dynamodb` CLI, `redis-cli`, or `cqlsh` installed depending on target database
- Documented list of application access patterns (read/write queries the application performs)
- Expected data volumes (document count, average document size, growth rate)
- Read/write ratio and latency requirements for each access pattern
- Understanding of consistency requirements (strong vs. eventual consistency)
## Instructions