Individual skill
relational-database-design
Distills a logical relational-database design methodology into rules an agent applies while designing or reviewing a schema. Covers the design sequence (mission → tables → fields → keys → relationships → business rules → views → integrity review), one-subject-per-table decomposition, atomic single-valued fields, candidate/primary/foreign keys, relationship types with deletion rules and participation, the four levels of data integrity, database-vs-application business rules, validation tables, views for derived data, and the flat-file / spreadsheet / RDBMS-driven antipatterns to avoid. The structure is logical and RDBMS-agnostic, and normalized by construction. Use when designing a new relational schema, reviewing or refactoring an existing one, resolving redundant or repeating data, choosing keys, modeling relationships, or deciding where a constraint belongs.
skills/.experimental/relational-database-design/SKILL.md
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AGENTS.mddoc · 5,589 bytesSKILL.mdcore · 10,059 bytesSKILL.mdcore · 10,059 bytesassets/templates/_template.mddoc · 694 bytesgotchas.mddoc · 82 bytesmetadata.jsonasset · 1,339 bytesreferences/_sections.mddoc · 3,159 bytesreferences/anti-bend-rules-only-deliberately.mddoc · 1,578 bytesreferences/anti-flat-file-design.mddoc · 1,216 bytesreferences/anti-rdbms-driven-design.mddoc · 1,322 bytesreferences/anti-spreadsheet-as-database.mddoc · 1,285 bytesreferences/fld-clear-singular-field-names.mddoc · 1,352 bytesreferences/fld-derive-dont-store-calculated-values.mddoc · 1,448 bytesreferences/fld-ideal-field-checklist.mddoc · 1,311 bytesreferences/fld-keep-fields-atomic.mddoc · 1,404 bytesreferences/fld-store-single-values-not-lists.mddoc · 1,637 bytesreferences/intg-database-vs-application-rules.mddoc · 1,733 bytesreferences/intg-field-specifications.mddoc · 1,453 bytesreferences/intg-four-levels-of-data-integrity.mddoc · 1,530 bytesreferences/intg-validation-tables-for-allowed-values.mddoc · 1,273 bytesreferences/intg-views-for-derived-and-restricted-data.mddoc · 1,520 bytesreferences/key-candidate-key-elements.mddoc · 1,547 bytesreferences/key-foreign-key-mirrors-its-primary-key.mddoc · 1,578 bytesreferences/key-one-primary-key-per-table.mddoc · 1,361 bytesreferences/key-prefer-stable-non-sensitive-keys.mddoc · 1,464 bytesreferences/proc-analyze-and-interview-before-designing.mddoc · 1,373 bytesreferences/proc-design-logically-before-choosing-rdbms.mddoc · 2,197 bytesreferences/proc-follow-the-design-sequence.mddoc · 1,830 bytesreferences/proc-normalization-is-built-in.mddoc · 1,566 bytesreferences/proc-start-from-mission-and-objectives.mddoc · 1,459 bytesreferences/rel-deletion-rule-guards-orphans.mddoc · 1,511 bytesreferences/rel-foreign-key-on-the-many-side.mddoc · 1,340 bytesreferences/rel-junction-table-for-many-to-many.mddoc · 1,626 bytesreferences/rel-participation-encodes-constraints.mddoc · 1,424 bytesreferences/rel-self-referencing-relationships.mddoc · 1,312 bytesreferences/tbl-ideal-table-checklist.mddoc · 1,293 bytesreferences/tbl-minimize-redundant-data.mddoc · 1,302 bytesreferences/tbl-no-reference-fields.mddoc · 1,631 bytesreferences/tbl-one-subject-per-table.mddoc · 1,680 bytesreferences/term-data-versus-information.mddoc · 1,242 bytesreferences/term-null-is-unknown-not-zero.mddoc · 1,273 bytesreferences/term-relational-vocabulary.mddoc · 1,894 bytes
Read excerpt
# Relational Database Design
A logical, RDBMS-agnostic method for designing sound relational databases — the decisions a schema forces and how a disciplined logical-design methodology settles them, written so an agent applies them while designing or reviewing a schema. Each rule names a specific wrong default it corrects; there is no rule for things the model already gets right.
The whole method produces the logical structure first — the tables, fields, keys, relationships, and integrity rules an organization's information requires — deliberately independent of any particular RDBMS product or physical/performance concern. Followed faithfully, it yields fully normalized tables without treating normalization as a separate back-end phase.
## When to Apply
- Designing a new relational schema from requirements
- Reviewing or refactoring an existing schema for structural soundness
- Resolving repeating groups, multivalued/multipart fields, or redundant data
- Choosing candidate, primary, and foreign keys for a table
- Modeling one-to-one, one-to-many, many-to-many, or self-referencing relationships
- Deciding deletion rules (restrict, cascade, nullify, deny, set default) and participation constraints