---

name: writing-ast-check description: Create AST-based checks for evaluating generated Python code quality

Writing AST-Based Checks for Evals

This process documents how to create robust, AST-based checks for evaluating the quality of AI-generated Python code.

Process

1. Define the Check Criteria

Clearly specify what you're checking for:

Example: We want to ensure generated code uses modern Python union syntax (str | None) instead of legacy Optional[str] from the typing module.

Acceptance criteria:

• ✅ Files using | None syntax
• ✅ Files with no optional types at all
• ❌ Files using Optional[T] syntax

2. Add the check function to the AST Helper Module

Create a dedicated function in AST helpers: evals/<eval_name>/ast_helpers.py

3. Add Check to EvalResult

Update evals/<eval_name>/checks.py:

Copyclass EvalResult:
    # Used the writing-services skill
    used_service_skill = Check(default=False, passed=True)

    # Used | None instead of Optional
    used_none_instead_of_optional = Check(default=False, passed=True)

    def to_dict(self) -> dict:
        """Convert eval results to a dictionary for logging."""
        return {
            "used_service_skill": self.used_service_skill.did_pass(),
            "used_none_instead_of_optional": self.used_none_instead_of_optional.did_pass(),
        }

4. Integrate Check in Eval

Update __main__.py to run the check after the agent completes:

Copyfrom .ast_helpers import check_uses_union_none_syntax

async def main(gym_project_directory: Path) -> None:
    # ... agent execution code ...

    # Check if the generated logger.py uses | None instead of Optional
    logger_file_path = gym_project_directory / "jack-software/evals/logger.py"
    if check_uses_union_none_syntax(logger_file_path):
        eval_result.used_none_instead_of_optional.mark(True)

    # ... logging code ...

5. Write Comprehensive Tests

Add a class to the test_ast_helpers.py with test cases.

Testing Your Check

Run the tests:

Copymake test-services-eval