What problem does it solve? DynamoDB designs fail in predictable ways — hot partitions, wrong GSI projections, unbounded Scans, surprise bills — and most mistakes are only discovered after deployment. This Skill produces a defensible DynamoDB data-layer design grounded in explicit access patterns and design axioms, with a monthly cost estimate and optional live benchmarking against real AWS resources before you commit. ## Core Features & Use Cases - Axiom-driven schema design: Enumerates access patterns, then chooses partition/sort keys, GSIs, single-table vs. multi-table layout, Streams, TTL, Global Tables, and capacity mode using a documented conflict-resolution ordering. - Cost estimation: Generates a monthly cost report from a JSON data model via scripts/calculate_costs.py, with per-attribute item-size walkthroughs to keep estimates accurate. - Live validation pipeline: Optionally deploys the schema to AWS, benchmarks it with an in-region Lambda (quick, standard, or representative load modes), generates a performance report, and tears everything down — with consent gates and spend guardrails at every billable step. - Use Case: You are designing a multi-tenant SaaS backend on DynamoDB. The Skill interviews you on per-entity operational requirements, produces the access-pattern list, schema, and per-pattern query plan, estimates the monthly bill, then deploys and load-tests the design in a sandbox account to surface hot-partition and GSI-amplification risks. ## Quick Start Ask the agent to design a DynamoDB data layer for your application by listing your entities and query requirements, and let it produce the access-pattern list, schema, and cost estimate.
