chore: import upstream snapshot with attribution

check/check_yaml.py

@@ -0,0 +1,46 @@
+"""Lightweight schema validation leveraging typed config loaders."""
+
+import argparse
+from pathlib import Path
+from typing import Any, List, Optional
+
+from entity.configs import ConfigError, DesignConfig
+from utils.io_utils import read_yaml
+
+
+def validate_design(data: Any, set_defaults: bool = True, fn_module_ref: Optional[str] = None) -> List[str]:
+    """Validate raw YAML data using the typed config loader.
+    
+    Note: This function validates schema structure only, without resolving
+    environment variable placeholders like ${VAR}. This allows workflows to
+    be saved even when environment variables are not yet configured - they
+    will be resolved at runtime.
+    """
+    try:
+        if not isinstance(data, dict):
+            raise ConfigError("YAML root must be a mapping", path="root")
+        # Use DesignConfig.from_dict directly to skip placeholder resolution
+        # Users may configure environment variables at runtime
+        DesignConfig.from_dict(data)
+        return []
+    except ConfigError as exc:
+        return [str(exc)]
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Validate workflow YAML structure against the typed config loader")
+    parser.add_argument("path", help="Path to the workflow YAML file")
+    args = parser.parse_args()
+
+    data = read_yaml(args.path)
+    errors = validate_design(data)
+    if errors:
+        print("Design validation failed:")
+        for err in errors:
+            print(f"- {err}")
+        raise SystemExit(1)
+    print("Design validation successful.")
+
+
+if __name__ == "__main__":
+    main()