Designing Database SchemasSAFE
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Overview
From the repository's own README, as read at the audited commit. Badges and raw HTML are left out.
Bundled resources for database-schema-designer skill
- [ ] example_schemas/: Directory containing example database schemas for various applications (e.g., e-commerce, social media, CRM).
- [ ] erd_examples/: Directory containing example ERD diagrams in Mermaid syntax.
4f83675ca38aOBSERVED · 2026-10-08Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| claude-code | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: designing-database-schemas description: 'Process use when you need to work with database schema design. This skill provides schema design and migrations with comprehensive guidance and automation. Trigger with phrases like "design schema", "create migration", or "model database". ' allowed-tools: Read, Write, Edit, Grep, Glob, Bash(psql:*), Bash(mysql:*), Bash(mongosh:*) version: 1.24.0 author: Jeremy Longshore <[email protected]> license: MIT tags: - database - migration - designing-database compatibility: Designed for Claude Code --- # Database Schema Designer ## Overview Design normalized relational database schemas from business requirements, entity-relationship diagrams, or existing application code. This skill produces PostgreSQL or MySQL DDL with proper data types, constraints, indexes, and relationships following normalization principles (3NF by default) with strategic denormalization where performance requires it. ## Prerequisites - Business domain requirements or existing application models/classes to derive schema from - `psql` or `mysql` CLI for testing schema DDL - Target database engine and version (determines available data types and features) - Expected data volumes and query patterns for sizing and index decisions - Multi-tenancy requirements (shared schema, schema-per-tenant, or database-per-tenant) ## Instructions 1. Identify all entities (nouns) from the business requirements. Each entity becomes a table. List every attribute (property) of each entity and classify as required or optional. 2. Define primary keys for each table. Prefer `BIGSERIAL` (PostgreSQL) or `BIGINT AUTO_INCREMENT` (MySQL) for surrogate keys. Use `UUID` (via `gen_random_uuid()`) for distributed systems or when IDs are exposed in URLs. Natural keys are acceptable when truly immutable and unique (ISO country codes, IATA airport codes). 3. Normalize the schema to Third Normal Form (3NF): - **1NF**: Eliminate repeating groups. Each column holds a single atomic value. No arrays in columns (unless using PostgreSQL array types intentionally). - **2NF**: Remove partial dependencies. Every non-key column depends on the entire primary key. - **3NF**: Remove transitive dependencies. Non-key columns depend only on the primary key, not on other non-key columns. Extract lookup tables for values that change independently. 4. Define relationships between tables: - **One-to-many**: Add a foreign key column on the "many" side referencing the "one" side. Example: `orders.customer_id REFERENCES customers(id)`. - **Many-to-many**: Create a junction table with two foreign keys. Example: `product_categories(product_id, category_id)` with a composite primary key. - **One-to-one**: Add a foreign key with a UNIQUE constraint, or merge into a single table if entities are always accessed together. 5. Choose appropriate data types with precision: - Money: `NUMERIC(12,2)` or `INTEGER` storing cents (never `FLOAT`/`DOUBLE`) - Timestamps: `TIMESTAMPTZ` (PostgreSQL) with time zone for events; `DATE` for calendar dates - Status fields: `VARCHAR(20)` with CHECK constraint, or create an ENUM type - Email: `CITEXT` (PostgreSQL) or `VARCHAR(254)` with CHECK constraint for format validation - JSON: `JSONB` (PostgreSQL) for flexible schema attributes; avoid for core relational data 6. Add standard columns to every table: - `created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()` - `updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW()` (with trigger for auto-update) - `deleted_at TIMESTAMPTZ` for soft delete (add partial index `WHERE deleted_at IS NULL`) 7. Define constraints: NOT NULL on required fields, UNIQUE on natural keys and email addresses, CHECK constraints for value validation (`CHECK (price >= 0)`, `CHECK (status IN ('active', 'inactive'))`), and foreign keys with appropriate ON DELETE behavior (CASCADE, SET NULL, or RESTRICT). 8. Design indexes based on expected query patterns: - Primary key index is automatic - Foreign key columns: always index these for JOIN performance - Columns in WHERE clauses with high selectivity: B-tree index - Full-text search columns: GIN index on `tsvector` - Composite indexes: match the most common multi-column filter patterns, leftmost column first 9. Apply strategic denormalization where 3NF causes unacceptable query complexity: - Materialized views for expensive aggregate queries - Denormalized counter columns (with trigger-based updates) for counts displayed on every page load - JSON columns for flexible metadata that varies by record type 10. Generate the complete DDL script with CREATE TABLE statements in dependency order (referenced tables first), followed by indexes, triggers, and any seed data for lookup tables. ## Output - **Complete DDL script** with CREATE TABLE, constraints, indexes, and triggers in executable order - **Entity-relationship description** listing all tables, columns, types, and relationships - **Index strategy document** explaining which indexes support which query patterns - **Seed data scripts** for lookup/reference tables (countries, statuses, categories) - **Migration file** compatible with the project's migration framework ## Error Handling | Error | Cause | Solution | |-------|-------|---------| | Circular foreign key dependency | Tables reference each other, preventing creation in any order | Use `ALTER TABLE ADD CONSTRAINT` after both tables are created; or redesign to eliminate the cycle with a junction table | | Over-normalization causing excessive JOINs | Every lookup value in its own table, queries require 8+ JOINs | Denormalize low-cardinality, rarely-changing lookup values; use ENUM types for status fields instead of separate tables | | NUMERIC precision overflow | Monetary values exceed `NUMERIC(10,2)` maximum | Increase precision to `NUMERIC(15,2)` or `NUMERIC(19,4)` for currencies requiring sub-cent precision | | Schema too rigid for evolving requirements
Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | PASS |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
4f83675ca38afull audit observations/trust-audit/skill/jeremylongshore__designing-database-schemas.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-08 | 4f83675ca38a | SAFE | B | 89 | first audit |
Questions
What does the Designing Database Schemas skill do?
Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.
Is Designing Database Schemas safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Designing Database Schemas access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does Designing Database Schemas work with?
Its documentation mentions claude-code. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (4f83675ca38a), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.