To get the best results from Codegen, treat it like a skilled teammate: provide clear, specific instructions and sufficient context. Vague requests lead to ambiguous outcomes.
Codegen is based on Anthropic’s Claude 3.7. You can prompt it similarly to ChatGPT or other LLM-based assistants

​
The Core Principle: Specificity

Instead of “Fix the user service,” try:
In the my-web-app repo (PR #42), refactor the UserService class in src/services/user.ts to use the UserRepository pattern shown in ProductService/ProductRepository.
If there are specific implementation details you want included, make sure to specify. For example:
Ensure all tests in tests/services/user.test.ts pass and add new tests for the repository with 90%+ coverage. Update the diagram in docs/architecture/user-service.md.

​
Elements of a Strong Prompt

  1. Scope: What repository, branch, or files are involved? (e.g., my-web-app repo, PR #42, src/services/user.ts)
  2. Goal: What is the high-level objective? (e.g., Refactor UserService, improve testability)
  3. Tasks: What specific actions should the agent take? Use a numbered or bulleted list for clarity. (e.g., Extract logic to UserRepository, use dependency injection, update tests, update diagram)
  4. Context/Patterns: Are there existing patterns, examples, or documentation to reference? (e.g., ProductService, ProductRepository)
  5. Success Criteria: How will you know the task is done correctly? (e.g., Tests pass, 90%+ coverage, diagram updated)
Clear, detailed prompts empower Codegen agents to deliver accurate results faster, significantly streamlining your workflow.