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Schema awareness - read before coding, type generation, prevent column errors
Passed 20 of 22 test cases with the skill, and 18 of 22 without it.
and 2 more in the full report
3 fixed17 passed either way1 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
What practice should be avoided when selecting columns or handling foreign key field names in ORM models?
| Checked | Without skill | With skill |
|---|---|---|
| Advises against guessing column names or foreign key relationships without inspecting the schema first. | Missed | Passed |
The instructions your model reads when the skill loads.
Problem: Claude forgets schema details mid-session - wrong column names, missing fields, incorrect types. TDD catches this at runtime, but we can prevent it earlier.
MANDATORY: Before writing ANY code that touches the database:
┌─────────────────────────────────────────────────────────────┐
│ 1. READ the schema file (see locations below) │
│ 2. VERIFY columns/types you're about to use exist │
│ 3. REFERENCE schema in your response when writing queries │
│ 4. TYPE-CHECK using generated types (Drizzle/Prisma/etc) │
└─────────────────────────────────────────────────────────────┘
If schema file doesn't exist → CREATE IT before proceeding.
| Stack | Schema Location | Type Generation |
|---|---|---|
| Drizzle | src/db/schema.ts or drizzle/schema.ts | Built-in TypeScript |
| Prisma | prisma/schema.prisma | npx prisma generate |
| Supabase | supabase/migrations/*.sql + types | supabase gen types typescript |
| SQLAlchemy | app/models/*.py or src/models.py | Pydantic models |
| TypeORM | src/entities/*.ts | Decorators = types |
| Raw SQL | schema.sql or migrations/ | Manual types required |
Create _project_specs/schema-reference.md for quick lookup:
test cases passed, vs 18 / 22 without
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