Schema Design
Migration-ready database schema design with normalization and indexing strategies
Best use case
Schema Design is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Migration-ready database schema design with normalization and indexing strategies
Teams using Schema Design should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/schema-design/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Schema Design Compares
| Feature / Agent | Schema Design | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Migration-ready database schema design with normalization and indexing strategies
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Schema Design ## Purpose Design relational database schemas with normalization trade-offs, migration plans, and indexing strategies. Produces migration-ready SQL that can be applied directly to the database. ## Inputs - Feature requirements (from interview/idea phase) - Existing schema (current tables, relationships, migrations) - Query patterns (how the data will be read — drives index and denormalization decisions) - Access control requirements (who can read/write which rows) ## Process ### Step 1: Inventory Existing Entities Read current schema files, migration history, or ORM models. List all existing tables with their columns, types, constraints, and relationships. Note any existing indexes and RLS policies. ### Step 2: Identify New Entities Needed From the feature requirements and interview output, determine what new data needs to be stored. List candidate entities and their purpose. ### Step 3: Define Entity Attributes For each new entity, define: - Column name, data type, and nullability - Default values and constraints (UNIQUE, CHECK, etc.) - Primary key strategy (UUID vs serial vs composite) - Timestamp columns (created_at, updated_at) ### Step 4: Map Relationships Define all relationships between entities: - **1:1** — Foreign key with UNIQUE constraint - **1:N** — Foreign key on the "many" side - **N:M** — Junction/through table with composite primary key - Document cascade behavior (ON DELETE CASCADE vs SET NULL vs RESTRICT) ### Step 5: Apply Normalization Default to 3NF. For each denormalization decision, document: - What is being denormalized - Why (query performance, read frequency, join cost) - How consistency is maintained (triggers, application logic, eventual consistency) ### Step 6: Design Indexes Drive index choices from query patterns: - Single-column indexes for filtered/sorted columns - Composite indexes for multi-column WHERE clauses (column order matters) - Partial indexes for filtered subsets (WHERE active = true) - GIN indexes for array/JSONB columns if applicable ### Step 7: Plan RLS Policies If using Supabase or row-level security: - Define SELECT, INSERT, UPDATE, DELETE policies per table - Map policies to user roles (anon, authenticated, service_role) - Use auth.uid() for user-scoped access - Document any service_role bypass patterns ### Step 8: Draft Migration SQL Write executable SQL: - CREATE TABLE statements for new tables - ALTER TABLE statements for existing table modifications - CREATE INDEX statements - RLS policy statements - Include a rollback section (DROP TABLE, DROP INDEX, etc.) ## Output Format ```markdown # Schema Design: [Feature Name] ## Entity Overview | Entity | Purpose | New/Modified | |--------|---------|-------------| | ... | ... | ... | ## Entity Definitions ### [entity_name] | Column | Type | Nullable | Default | Constraints | |--------|------|----------|---------|-------------| | id | uuid | NO | gen_random_uuid() | PK | | ... | ... | ... | ... | ... | ## Relationships ``` [ASCII diagram] users 1──N posts posts N──M tags (through: post_tags) ``` ## Index Strategy | Table | Index | Columns | Type | Rationale | |-------|-------|---------|------|-----------| | ... | ... | ... | ... | ... | ## Denormalization Decisions | What | Why | Consistency Strategy | |------|-----|---------------------| | ... | ... | ... | ## RLS Policies | Table | Operation | Policy | Using | |-------|-----------|--------|-------| | ... | ... | ... | ... | ## Migration SQL ### Up ```sql -- New tables CREATE TABLE ... -- Indexes CREATE INDEX ... -- RLS ALTER TABLE ... ENABLE ROW LEVEL SECURITY; CREATE POLICY ... ``` ### Down ```sql DROP POLICY ... DROP INDEX ... DROP TABLE ... ``` ``` ## Quality Checks - [ ] Every entity has a primary key - [ ] Foreign keys reference existing or newly created tables - [ ] Indexes support the identified query patterns - [ ] Migration is reversible (Down section undoes Up completely) - [ ] RLS policies cover all access patterns (SELECT, INSERT, UPDATE, DELETE) - [ ] Timestamp columns (created_at, updated_at) are present on mutable entities - [ ] CASCADE behavior is explicitly defined for all foreign keys - [ ] No orphan tables (every table is reachable via relationships or has a documented reason for isolation) ## Evolution Notes <!-- Observations appended after each use -->
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