writing-ast-check
Create AST-based checks for evaluating generated Python code quality
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install jack-michaud-faire-writing-ast-check
Repository
Skill path: .claude/skills/writing-ast-check
Create AST-based checks for evaluating generated Python code quality
Open repositoryBest for
Primary workflow: Write Technical Docs.
Technical facets: Full Stack, Tech Writer.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: jack-michaud.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install writing-ast-check into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/jack-michaud/faire before adding writing-ast-check to shared team environments
- Use writing-ast-check for development workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
---
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`:
```python
class 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:
```python
from .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:
```bash
make test-services-eval
```