Dc import info skill

[rohitkumarbhagat]

No description provided.

[gemini-code-assist]

Code Review

This pull request introduces a read-only agent support framework (dc-import-info skill) for inspecting Data Commons import extraction and transformation (ET) pipelines. It adds structured operational recipes (GCP Batch, GCS, Logging, Scheduler, Spanner, and local), architectural references, environment configuration defaults, and Python helper scripts with unit tests. Feedback on the changes suggests defensively stripping whitespace from absolute_import_name in the GCS summary-list helper to prevent validation failures, and adding a conditional check in the Scheduler describe-job recipe's jq command to robustly handle missing or null HTTP target bodies.

[gemini-code-assist]

The absolute_import_name is matched against _IMPORT_NAME_PATTERN without stripping leading or trailing whitespace. If a user or agent passes an input with accidental surrounding whitespace, the validation will fail. Stripping the input defensively ensures robustness.

def normalize_import_name(absolute_import_name: str) -> dict[str, str]:
    """Validates an absolute import name and derives its exact GCS prefix."""
    absolute_import_name = absolute_import_name.strip()
    match = _IMPORT_NAME_PATTERN.fullmatch(absolute_import_name)

[gemini-code-assist]

The jq expression (.httpTarget.body | @base64d | fromjson | .argument.importName) will throw an error and crash the command if .httpTarget.body is null or missing (e.g., if the Scheduler job is misconfigured or uses a different target type). Adding a conditional check makes the recipe more robust.

Suggested change

	target_uri: .httpTarget.uri,
	target_import_name:
	(.httpTarget.body | @base64d | fromjson | .argument.importName)}'
	target_uri: .httpTarget.uri,
	target_import_name:
	(if .httpTarget.body then (.httpTarget.body | @base64d | fromjson | .argument.importName) else null end)}'