database-schema
by alinaqidatabase-schema helps agents read the database contract before writing queries, migrations, or model code. It reduces wrong column names, missing fields, and type mismatches by checking schema files and generated types first. Use this database-schema guide for safer Database Engineering workflows.
This skill scores 79/100, which means it is a solid directory candidate for users who want schema-first database work with less guesswork than a generic prompt. It is triggerable and operationally useful, though users should note some missing packaging and support-file polish before relying on it broadly.
- Explicit trigger and use case: 'Before writing any code that touches the database' with when-to-use guidance and path patterns for schema, migrations, models, and ORM files.
- Operational workflow is concrete: read schema first, verify columns/types, reference schema in responses, and type-check generated types.
- Substantial content depth: long SKILL.md with many headings, code fences, repo/file references, and constraint-oriented guidance rather than a stub.
- No install command and no support files (scripts, references, resources, or rules), so adoption depends almost entirely on the SKILL.md instructions.
- Placeholder markers ('todo') appear in the skill body, suggesting some sections may still be incomplete or need cleanup.
Overview of database-schema skill
What database-schema does
The database-schema skill helps an AI read the database contract before it writes queries, migrations, or model code. If you work in Database Engineering, this is the skill to use when you want fewer wrong column names, missing fields, type mismatches, and silent assumptions about table structure.
Who should use it
Use the database-schema skill if your task depends on existing tables, generated types, or migration history. It is most useful for engineers editing app code, agents generating SQL, or anyone asked to change data access safely without guessing the schema.
Why it matters in practice
The main value is not abstract “schema awareness”; it is preventing avoidable breakage early. The skill pushes the model to inspect the schema source of truth, confirm field names and types, and align generated code with that contract before writing database logic.
How to Use database-schema skill
Install and activate it
For a database-schema install, add the skill to your Claude skills setup and then point your agent at a task that touches persistence. In the repo, the skill is defined as non-user-invocable, so it is meant to be triggered by workflow context rather than called as a standalone command.
Give it the right input
A good database-schema usage prompt should include the stack, the files involved, and the exact database task. For example: “Update the user profile API to write display_name and timezone in our Drizzle schema; check the schema first and confirm the types.” That is better than “fix the database code” because it gives the skill a concrete target and a place to verify it.
Read the right files first
Start with SKILL.md, then inspect the schema source for your stack: schema.ts, schema.prisma, migration SQL, or model files. If the repository has generated types, review them too, because the skill is designed to use schema plus type generation as a safety check, not schema alone.
Use a schema-first workflow
The most effective workflow is: identify the table or model, verify the exact columns and constraints, map your task to those fields, then write code or SQL that matches. If the schema is missing, the skill’s guidance is to create it before proceeding rather than inventing table shape in the application layer.
database-schema skill FAQ
Is database-schema only for one ORM?
No. The database-schema skill is useful across stacks because it centers the same habit: read the schema before writing code. The repository explicitly references Drizzle, Prisma, Supabase, SQLAlchemy, and TypeORM-style model locations.
Is this better than a normal prompt?
Yes, when the task depends on accurate database structure. A generic prompt may produce plausible SQL, but this skill adds a workflow constraint: confirm schema and types first, then generate code from that verified contract.
Is it beginner-friendly?
Mostly yes, if the user can identify the project’s schema files. Beginners benefit because the skill reduces guesswork, but they still need to know where their schema lives and whether the project uses migrations, ORM models, or generated types.
When should I not use it?
Do not rely on database-schema when the task is unrelated to persistence, or when the schema is intentionally fluid and no source of truth exists yet. It is also less useful for pure frontend work, documentation-only changes, or quick throwaway prototypes with no real database contract.
How to Improve database-schema skill
Give it a sharper schema target
The biggest upgrade is naming the specific entity and operation: “add last_login_at to users and update the read path” is far stronger than “change auth.” Clearer targets help the database-schema skill verify the correct table, relation, and type before writing.
Include constraints and edge cases
If the task has uniqueness rules, nullable fields, foreign keys, soft deletes, or existing data to preserve, say so upfront. These details matter because they change the safe shape of the query or migration and reduce the chance of a schema-aware but still incorrect implementation.
Ask for verification, not just code
A strong database-schema guide request should ask the model to confirm the schema assumptions it used and to call out anything ambiguous. That extra step catches cases where the repository has multiple schema files, generated types are stale, or the model must choose between similar columns.
Iterate from the first draft
After the first output, refine based on what was missing: a migration path, a type update, or a compatibility note for existing rows. The best database-schema results come from a short loop of “verify schema, write code, compare against contract, then revise” rather than one-shot generation.