comparing-database-schemas
Process use when you need to work with schema comparison. This skill provides database schema diff and sync with comprehensive guidance and automation. Trigger with phrases like "compare schemas", "diff databases", or "sync database schemas".
Best use case
comparing-database-schemas is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Process use when you need to work with schema comparison. This skill provides database schema diff and sync with comprehensive guidance and automation. Trigger with phrases like "compare schemas", "diff databases", or "sync database schemas".
Teams using comparing-database-schemas 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/comparing-database-schemas/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How comparing-database-schemas Compares
| Feature / Agent | comparing-database-schemas | 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?
Process use when you need to work with schema comparison. This skill provides database schema diff and sync with comprehensive guidance and automation. Trigger with phrases like "compare schemas", "diff databases", or "sync database schemas".
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.
Related Guides
Best AI Skills for Claude
Explore the best AI skills for Claude and Claude Code across coding, research, workflow automation, documentation, and agent operations.
ChatGPT vs Claude for Agent Skills
Compare ChatGPT and Claude for AI agent skills across coding, writing, research, and reusable workflow execution.
Top AI Agents for Productivity
See the top AI agent skills for productivity, workflow automation, operational systems, documentation, and everyday task execution.
SKILL.md Source
# Database Diff Tool ## Overview Compare database schemas between two environments (development vs. staging, staging vs. ## Prerequisites - Connection credentials to both source and target databases - `psql` or `mysql` CLI configured to connect to both environments - Read access to `information_schema` and `pg_catalog` (PostgreSQL) or `information_schema` (MySQL) - Permission to run `pg_dump --schema-only` for full schema extraction - Understanding of which environment is the "source of truth" (typically the migration-managed environment) ## Instructions 1. Extract the full schema from both databases for comparison: - PostgreSQL: `pg_dump --schema-only --no-owner --no-privileges -f schema_source.sql source_db` and repeat for target_db - MySQL: `mysqldump --no-data --routines --triggers source_db > schema_source.sql` - Alternatively, query `information_schema` directly for programmatic comparison 2. Compare tables present in each database: - `SELECT table_name FROM information_schema.tables WHERE table_schema = 'public' AND table_catalog = 'source_db' EXCEPT SELECT table_name FROM information_schema.tables WHERE table_schema = 'public' AND table_catalog = 'target_db'` - This reveals tables that exist in source but not in target (and vice versa) 3. Compare columns for each shared table: - Query `information_schema.columns` from both databases for: `column_name`, `data_type`, `character_maximum_length`, `is_nullable`, `column_default`, `ordinal_position` - Flag differences in data type, nullability, default values, and column ordering - Detect added columns (in source, not target) and dropped columns (in target, not source) 4. Compare indexes: - PostgreSQL: Query `pg_indexes` for `indexname`, `indexdef` on each database - MySQL: Query `information_schema.STATISTICS` for `INDEX_NAME`, `COLUMN_NAME`, `NON_UNIQUE` - Flag missing, extra, or differently-defined indexes 5. Compare constraints (primary keys, foreign keys, unique, check): - Query `information_schema.table_constraints` and `information_schema.key_column_usage` - Detect missing foreign keys, changed constraint names, and altered check constraint expressions 6. Compare functions, stored procedures, and triggers: - PostgreSQL: Query `pg_proc` for function signatures and `pg_trigger` for trigger definitions - MySQL: Query `information_schema.ROUTINES` and `information_schema.TRIGGERS` - Compare function bodies for logical differences 7. Compare enum types and custom types (PostgreSQL): - Query `pg_type` and `pg_enum` for enum label differences - Detect added or removed enum values (note: PostgreSQL only supports adding enum values, not removing) 8. Generate a structured diff report categorizing differences as: - **Added**: Objects in source not present in target (require CREATE statements) - **Removed**: Objects in target not present in source (require DROP statements, confirm intentional) - **Modified**: Objects differing between source and target (require ALTER statements) 9. Generate migration SQL to synchronize the target database to match the source: - CREATE TABLE for new tables, ALTER TABLE ADD COLUMN for new columns - ALTER TABLE ALTER COLUMN for type changes, ALTER TABLE DROP COLUMN for removed columns - CREATE INDEX / DROP INDEX for index differences - Include transaction wrapping and rollback-safe operations 10. Validate the generated migration by applying it to a copy of the target database and re-running the diff. The second diff should report zero differences, confirming the migration produces the expected state. ## Output - **Schema diff report** listing all differences categorized by type (added, removed, modified) - **Migration SQL script** to synchronize target schema to match source - **Rollback SQL script** to reverse the migration if needed - **Side-by-side comparison** of differing object definitions - **Drift detection summary** highlighting changes not tracked in migration files ## Error Handling | Error | Cause | Solution | |-------|-------|---------| | Connection refused to one database | Network or credential issue on source or target | Verify connection strings; check firewall rules; confirm credentials work with direct `psql` or `mysql` connection | | Permission denied on `pg_catalog` queries | User lacks read access to system catalogs | Grant `pg_read_all_settings` role; or use `pg_dump --schema-only` which requires fewer privileges | | False positive differences from default value formatting | PostgreSQL normalizes default expressions differently in different versions | Normalize default value strings before comparison; ignore whitespace differences; compare semantic equivalence | | Enum type modification blocked | PostgreSQL does not support removing enum values or reordering | Create a new enum type, migrate the column, drop the old type; document this as a multi-step migration | | Generated migration fails on target | Target has data that violates new constraints | Add data validation queries before constraint creation; backfill default values; handle edge cases in migration | ## Examples **Detecting schema drift between staging and production**: After 3 months without auditing, the diff reveals: 2 columns added to production manually (not in migrations), 1 index missing from staging, and 3 functions with different implementations. A migration script is generated to bring staging in sync, and the manual production changes are backported into migration files. **Pre-deployment schema validation**: Before deploying a release with 5 migration files, run the diff between the post-migration staging schema and the expected schema. The diff catches a migration that accidentally dropped a constraint that a later migration depends on. The migration ordering is fixed before production deployment. **Comparing PostgreSQL schemas across major version upgrade**: Schema extracted from PostgreSQL 14 and compared against PostgreSQL 16 after migration. Diff reveals function signature changes for built-in function calls, updated default values for new parameters, and deprecated syntax in stored procedures. Migration script updates function definitions for the new version. ## Resources - PostgreSQL information_schema: https://www.postgresql.org/docs/current/information-schema.html - MySQL information_schema: https://dev.mysql.com/doc/refman/8.0/en/information-schema.html - pg_dump schema-only mode: https://www.postgresql.org/docs/current/app-pgdump.html - migra (PostgreSQL schema diff tool): https://github.com/djrobstep/migra - Skeema (MySQL schema management): https://www.skeema.io/
Related Skills
managing-database-tests
Test database testing including fixtures, transactions, and rollback management. Use when performing specialized testing. Trigger with phrases like "test the database", "run database tests", or "validate data integrity".
monitoring-database-transactions
Monitor use when you need to work with monitoring and observability. This skill provides health monitoring and alerting with comprehensive guidance and automation. Trigger with phrases like "monitor system health", "set up alerts", or "track metrics".
managing-database-sharding
Process use when you need to work with database sharding. This skill provides horizontal sharding strategies with comprehensive guidance and automation. Trigger with phrases like "implement sharding", "shard database", or "distribute data".
scanning-database-security
Process use when you need to work with security and compliance. This skill provides security scanning and vulnerability detection with comprehensive guidance and automation. Trigger with phrases like "scan for vulnerabilities", "implement security controls", or "audit security".
designing-database-schemas
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".
managing-database-replication
Process use when you need to work with database scalability. This skill provides replication and sharding with comprehensive guidance and automation. Trigger with phrases like "set up replication", "implement sharding", or "scale database".
managing-database-recovery
Process use when you need to work with database operations. This skill provides database management and optimization with comprehensive guidance and automation. Trigger with phrases like "manage database", "optimize database", or "configure database".
managing-database-partitions
Process use when you need to work with database partitioning. This skill provides table partitioning strategies with comprehensive guidance and automation. Trigger with phrases like "partition tables", "implement partitioning", or "optimize large tables".
managing-database-migrations
Process use when you need to work with database migrations. This skill provides schema migration management with comprehensive guidance and automation. Trigger with phrases like "create migration", "run migrations", or "manage schema versions".
analyzing-database-indexes
Process use when you need to work with database indexing. This skill provides index design and optimization with comprehensive guidance and automation. Trigger with phrases like "create indexes", "optimize indexes", or "improve query performance".
monitoring-database-health
Monitor use when you need to work with monitoring and observability. This skill provides health monitoring and alerting with comprehensive guidance and automation. Trigger with phrases like "monitor system health", "set up alerts", or "track metrics".
detecting-database-deadlocks
Process use when you need to work with deadlock detection. This skill provides deadlock detection and resolution with comprehensive guidance and automation. Trigger with phrases like "detect deadlocks", "resolve deadlocks", or "prevent deadlocks".