scaffolding-oracle-to-postgres-migration-test-project
by github
Scaffolds an xUnit integration test project for validating Oracle-to-PostgreSQL database migration behavior in .NET solutions. Creates the test project,…
npx skills add https://github.com/github/awesome-copilot --skill scaffolding-oracle-to-postgres-migration-test-projectScaffolding an Integration Test Project for Oracle-to-PostgreSQL Migration
Creates a compilable, empty xUnit test project with transaction management and seed data infrastructure for a single target project. Run once per project before writing tests.
Workflow
Progress:
- [ ] Step 1: Inspect the target project
- [ ] Step 2: Create the xUnit test project
- [ ] Step 3: Implement transaction-rollback base class
- [ ] Step 4: Implement seed data manager
- [ ] Step 5: Verify the project compiles
Step 1: Inspect the target project
Read the target project's .csproj to determine the .NET version and existing package references. Match these versions exactly — do not upgrade.
Step 2: Create the xUnit test project
- Target the same .NET version as the application under test.
- Add NuGet packages for Oracle database connectivity and xUnit.
- Add a project reference to the target project only — no other application projects.
- Add an
appsettings.jsonconfigured for Oracle database connectivity.
Step 3: Implement transaction-rollback base class
- Create a base test class that opens a transaction before each test and rolls it back after.
- Catch and handle all exceptions to guarantee rollback.
- Make the pattern inheritable by all downstream test classes.
Step 4: Implement seed data manager
- Create a global seed manager for loading test data within the transaction scope.
- Do not commit seed data — transactions roll back after each test.
- Do not use
TRUNCATE TABLE— preserve existing database data. - Reuse existing seed files if available.
- Establish a naming convention for seed file location that downstream test creation will follow.
Step 5: Verify the project compiles
Build the test project and confirm it compiles with zero errors before finishing.
Key Constraints
- Oracle is the golden behavior source — scaffold for Oracle first.
- Keep to existing .NET and C# versions; do not introduce newer language or runtime features.
- Output is an empty test project with infrastructure only — no test cases.
More skills from github
console-rendering
github
Instructions for using the struct tag-based console rendering system in Go
official
acquire-codebase-knowledge
github
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document…
official
acreadiness-assess
github
Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc…
official
acreadiness-generate-instructions
github
Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS…
official
acreadiness-policy
github
Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting…
official
add-educational-comments
github
Add educational comments to code files to transform them into effective learning resources. Adapts explanation depth and tone to three configurable knowledge levels: beginner, intermediate, and advanced Automatically requests a file if none is provided, with numbered list matching for quick selection Expands files by up to 125% using educational comments only (hard limit: 400 new lines; 300 for files over 1,000 lines) Preserves file encoding, indentation style, syntax correctness, and...
official
adobe-illustrator-scripting
github
Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate…
official
agent-governance
github
Declarative policies, intent classification, and audit trails for controlling AI agent tool access and behavior. Composable governance policies define allowed/blocked tools, content filters, rate limits, and approval requirements — stored as configuration, not code Semantic intent classification detects dangerous prompts (data exfiltration, privilege escalation, prompt injection) before tool execution using pattern-based signals Tool-level governance decorator enforces policies at function...
official