mcpbeat

Datalineage Bigquery Asset Impact Analysis

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.

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Install

one command, takes just this skill from the repository
npx skills add https://github.com/google/skills --skill datalineage-bigquery-asset-impact-analysis

What comes with it

1 243 bytes besides the instruction
references/mcp-usage.md

The instruction itself

11 sections, as written by the author

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.

Prerequisites

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.

Analysis Workflow

1. Resolve the Asset's Fully Qualified Name (FQN)

  • Ensure you have the correct FQN format for the BigQuery asset:
  • *Format:* bigquery:{project_id}.{dataset_id}.{table_or_view_id}
  • *Example:* bigquery:my-prod-project.analytics.orders

2. Determine Locations and Parent Path

Identify the locations to search and construct the Data Lineage API request:

  • Discover Asset Location: Run the command `bq show --format=json

{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.

  • Set Parent Path: Set the parent path using the project ID and the

MCP 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}.

  • Configure Search Scope: Include the discovered asset location in the

locations array of the payload (e.g., ["us-central1"] or `["us",

"us-central1"]`).

3. Retrieve the Downstream Lineage Graph

Call the DataLineageServer:search_lineage tool to fetch downstream

relationships.

  • Direction: Set to DOWNSTREAM.
  • Search Parameters: Use max_depth = 10 and max_process_per_link = 5

as robust defaults.

4. Identify the Blast Radius

Traverse the returned lineage links to build the impact graph:

  • Affected Assets: The target of each link represents a downstream asset

that depends on your source asset.

  • Transform Processes: Inspect the processes field on each link. This

identifies the ETL pipelines, BigQuery Views, or Scheduled Queries that

propagate the data.

  • Direct vs. Indirect Impact:
  • Direct Impact (Depth 1): Assets directly consuming the source asset.

If a link has dependency_type: EXACT_COPY, mark the target as

"Directly Stale / Identical Copy".

  • Indirect Impact (Depth > 1): Assets further down the stream that

will experience cascading stale data or failures.

5. Summarize and Format the Output

Present your findings clearly to the user using the following structure:

  • Executive Summary: State the total number of downstream assets affected

and the maximum depth of the impact.

  • Critical Path: Highlight high-priority downstream assets (e.g., assets

containing "prod", "dashboard", "reporting", or "master" in their names).

  • Blast Radius Table: A clean Markdown table listing the dependencies. You

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 |

  • Analysis Metadata: Provide transparency on the parameters and boundaries

of your search so the user can choose to expand them:

  • Locations Searched: {list_of_locations_queried}
  • Parent Location: {parent_path}
  • Depth Limit: {max_depth}
  • Process per Link Limit: {max_process_per_link}
  • *Tip for User*: Let the user know they can request to rerun the analysis

with expanded locations or larger depth limits.

Crucial Constraints & Guardrails

  • Interpret Empty Responses Correctly:
  • If the lineage response is empty, immediately assume that no

dependencies exist in the queried locations and report this to the

user.

  • Strictly Banned Bypasses:
  • Exclusively retrieve downstream relationships using the

DataLineageServer:search_lineage tool.

  • Verify Asset Existence First:
  • If bq show indicates the source table does not exist, stop and report

this directly to the user. Do not attempt to guess alternative table

names unless the user explicitly instructs you to do so.

  • No Output Shortcutting or Hallucinated Artifacts:
  • Present the complete downstream blast radius table directly in your

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.

Reference Directory

  • MCP Usage: Using the Google Cloud Data Lineage

remote MCP server and tool preferences.

External Documentation

How to use it

Copy the folder

Take google/datalineage-bigquery-asset-impact-analysis from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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.