google/datalineage-bigquery-asset-impact-analysis
>- Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected.
npx skills add https://github.com/google/skills --skill datalineage-bigquery-asset-impact-analysis
This skill guides the agent in performing a downstream impact analysis (blast
radius assessment) when a BigQuery table or view is reported as broken, stale,
missing, or when a user is planning maintenance and wants to know the
consequences of modifying or pausing updates to an asset.
It relies primarily on the Google Cloud Data Lineage (Knowledge Catalog) MCP Server
to discover relationships between assets.
This skill requires access to the Google Cloud Data Lineage API and an active
client connection to the Data Lineage MCP Server. For detailed connection
configurations and tool schemas, refer to MCP Usage.
bigquery:{project_id}.{dataset_id}.{table_or_view_id}bigquery:my-prod-project.analytics.ordersIdentify the locations to search and construct the Data Lineage API request:
{project_id}:{dataset_id} and extract the location` field (e.g.,
us-central1 or us). If location discovery fails due to permissions or
missing tools, prompt the user for the dataset's location.
parent path using the project ID and theMCP server's location. Consult the DataLineageServer tool definition
to find the configured region or location (e.g., us). The format is:
projects/{project_id}/locations/{mcp_server_location}.
locations array of the payload (e.g., ["us-central1"] or `["us",
"us-central1"]`).
Call the DataLineageServer:search_lineage tool to fetch downstream
relationships.
DOWNSTREAM.max_depth = 10 and max_process_per_link = 5as robust defaults.
Traverse the returned lineage links to build the impact graph:
target of each link represents a downstream assetthat depends on your source asset.
processes field on each link. Thisidentifies the ETL pipelines, BigQuery Views, or Scheduled Queries that
propagate the data.
If a link has dependency_type: EXACT_COPY, mark the target as
"Directly Stale / Identical Copy".
will experience cascading stale data or failures.
Present your findings clearly to the user using the following structure:
and the maximum depth of the impact.
containing "prod", "dashboard", "reporting", or "master" in their names).
MUST include all columns:
| Downstream Asset | Transform Process | Depth | Impact Type |
| :------------------------------- | :------------------------------------ | :---- | :---------- |
| bigquery:project.dataset.table | projects/p/locations/l/processes/proc | 1 | Direct |
| bigquery:project.dataset.view | projects/p/locations/l/processes/view | 2 | Indirect |
of your search so the user can choose to expand them:
{list_of_locations_queried}{parent_path}{max_depth}{max_process_per_link}with expanded locations or larger depth limits.
dependencies exist in the queried locations and report this to the
user.
DataLineageServer:search_lineage tool.
bq show indicates the source table does not exist, stop and reportthis directly to the user. Do not attempt to guess alternative table
names unless the user explicitly instructs you to do so.
final response. Avoid telling the user you have created a separate
Markdown file or artifact containing the details unless you have
explicitly executed file-writing tools to create it.
remote MCP server and tool preferences.
Take google/datalineage-bigquery-asset-impact-analysis from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.