Database Schema Design
SkillDatabases & dataDesign relational or document schemas from access patterns, cardinality, and lifecycle. Use when modeling entities, choosing embed vs normalize, or shaping schema boundaries before implementation.
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Then ask your AI: use the Database Schema Design skill
What this skill tells your AI
The instructions your AI receives, as published by hoangnguyen0403/agent-skills-standard in skills/database/database-schema-design/SKILL.md and read by ahel’s review.
Priority: P0 (CRITICAL)
Start from reads, writes, and ownership. Schema follows access patterns, not vice versa.
Rules
- Model one business concept per table/collection boundary.
- Choose embed vs reference or normalize vs denormalize from cardinality, update frequency, and read locality.
- Encode uniqueness, nullability, and foreign-key or ownership rules explicitly.
- Prefer additive evolution over destructive redesigns.
Verify
- Hot reads are supported without avoidable joins or fan-out.
- Cardinality and lifecycle were written down for major relationships.
- Constraints or validation rules exist for business invariants.
- IDs, timestamps, and soft-delete semantics are consistent.
Anti-Patterns
- No schema from ORM defaults: model business access patterns first.
- No many-to-many without owner rules: define source of truth and cleanup behavior.
- No nullable drift: nullable fields need lifecycle meaning.
References
Signals
- GitHub stars
- 565
- Forks
- 163
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
database-schema-design-hoangnguyen0403- Source
- github.com/hoangnguyen0403/agent-skills-standard