creating-oracle-to-postgres-migration-integration-tests
Enables your agent to create integration tests for Oracle to PostgreSQL data migration. It captures expected behavior as a baseline.
What it does
This tool creates automatic tests to check how your program interacts with the Oracle database. It ensures the program works correctly with Oracle before being adapted for PostgreSQL.
When to use it
- ✓When you are starting to prepare for migrating from Oracle to PostgreSQL.
- ✓Before any migration work to PostgreSQL has begun.
- ✓To ensure tests function with Oracle as the baseline.
Example of what to ask your AI
“Create integration tests for my data access project that connects to Oracle.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool analyzes your code, creates sample data in Oracle, and writes tests that verify the code behaves as expected. These tests are designed to be easily adapted for PostgreSQL later.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add github/awesome-copilot --skill creating-oracle-to-postgres-migration-integration-testsOr download just the file:
curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/creating-oracle-to-postgres-migration-integration-tests/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Creating Integration Tests for Oracle-to-PostgreSQL Migration
Generates integration test cases for data access artifacts in a single target project. Tests target Oracle and capture its behavior as the authoritative baseline. They are written to be logically portable — so they can survive Phase 6 migration without rewriting — but they do not run against PostgreSQL at this stage.
Prerequisites
- The test project must already exist and compile (scaffolded separately).
- Read the existing base test class and seed manager conventions before writing tests.
Workflow
Test Creation:
- [ ] Step 1: Discover the test project conventions
- [ ] Step 2: Identify testable data access artifacts
- [ ] Step 3: Create seed data
- [ ] Step 4: Write test cases
- [ ] Step 5: Review determinism
Step 1: Discover the test project conventions
Read the base test class, seed manager, and project file to understand inheritance patterns, transaction management, and seed file conventions.
Step 2: Identify testable data access artifacts
Scope to the target project only. List data access methods that interact with the database — repositories, DAOs, stored procedure callers, query builders.
Step 3: Create seed data
- Follow seed file location and naming conventions from the existing project.
- Avoid
TRUNCATE TABLE— keep existing database data intact. - Assume existing business rows and lookup rows are already present; add only minimal, collision-safe seed records needed for the scenario.
- Do not commit seed data; tests run in transactions that roll back.
- Ensure seed data does not conflict with other tests.
- Load and verify seed data before assertions depend on it.
- Create or reuse a test
LookupConstantsclass for stable lookup IDs/codes used across seed builders and assertions.
Step 4: Write test cases
- Inherit from the base test class to get automatic transaction create/rollback.
- Ensure each database-touching method in scope has at least one integration test (or multiple tests for higher-risk behavior branches).
- Assert logical outputs (rows, columns, counts, error types), not platform-specific messages.
- Assert specific expected values — never assert that a value is merely non-null or non-empty when a concrete value is available from seed data.
- Avoid testing code paths that do not exist or asserting behavior that cannot occur.
- Avoid redundant assertions across tests targeting the same method.
- For text parameters, include both empty-string and
NULL/missing input coverage where applicable. - For datetime behavior, include assertions that validate the value written and read back matches — use the Oracle column's precision (e.g., seconds-only for a date/time column with no fractional seconds) rather than assuming any particular database type syntax.
Step 5: Review determinism
Re-examine every assertion against non-null values. Confirm each is deterministic against the seeded data. Fix any assertion that depends on database state outside the test's control.
Key Constraints
- Phase 3 only — these tests target Oracle. Do not invoke this skill during Phase 6 or against a PostgreSQL-targeting project.
- Oracle is the golden source — tests capture Oracle's expected behavior.
- Assertion portability — avoid platform-specific error messages or syntax in assertions so that when the test project is migrated to PostgreSQL in Phase 6, assertions require no changes.
- Seed only against Oracle — the test project will be migrated to PostgreSQL in Phase 6; seed data and infrastructure stay Oracle-targeted until then.
- Scoped to one project — do not create tests for artifacts outside the target project.
- Preserve existing data — never rewrite or wipe pre-existing business or lookup rows.
FAQ
What are 'data access artifacts'?
These are the parts of your code that directly communicate with the database to retrieve or save information.
Why use Oracle as the 'authoritative source'?
Because Oracle is the current system. The tests ensure everything works well with it before switching to PostgreSQL.
Can I use this after the project has already been migrated to PostgreSQL?
No, this tool is only for the preparation phase, before migration. It only works with Oracle.
Details
Original description by the author
Creates integration test cases targeting Oracle for .NET data access artifacts. Tests capture Oracle expected behavior as the authoritative baseline; they are written once and later ported to PostgreSQL by migrating the test project in Phase 6. Use only during Phase 3, before any PostgreSQL migration work has begun. Do not invoke during Phase 6 or against a project that has already been migrated.
repo: github/awesome-copilot
Popularity
- GitHub stars
- 40k
- Ranking position
- #5093
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
More skills from this repository
acquire-codebase-knowledge
Helps your agent understand and document an existing code project. It's useful for onboarding new people or getting an overview of the architecture.
github/awesome-copilot
acreadiness-assess
Enables your agent to assess a project's readiness for AI and generate a report. It's useful for understanding how well a project is prepared to use AI tools.
github/awesome-copilot
acreadiness-generate-instructions
Helps your agent create instructions for AI tools based on an assessment. It's useful for improving how AI interacts with code and closing identified gaps.
github/awesome-copilot
acreadiness-policy
Enables your agent to help define or apply policies for AI project assessment. It's useful for standardizing how projects are evaluated and ensuring compliance.
github/awesome-copilot
Similar skills
cpp-testing
Makes your agent write and improve tests for C++ code. It helps set up testing tools and fix errors.
affaan-m/ECC
csharp-testing
Helps your agent create tests for C# and .NET code. It uses best practices to ensure tests are efficient and reliable.
affaan-m/ECC
django-tdd
Enables your agent to apply testing strategies for Django with pytest-django and TDD. It's useful for writing robust tests and ensuring code quality, especially for DRF APIs.
affaan-m/ECC