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/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. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. -

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google-skills
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Install
$ npx -y skills add google/skills --skill datalineage-bigquery-asset-impact-analysis --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/datalineage-bigquery-asset-impact-analysis

Context preview

The summary Claude sees to decide when to auto-load this skill.

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. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. -

SKILL.md

datalineage-bigquery-asset-impact-analysis.SKILL.md
name: datalineage-bigquery-asset-impact-analysis
metadata:
  category: BigDataAndAnalytics
description: >-
  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.
  Use when:
  - Performing a blast radius or impact analysis for a BigQuery table or view.
  - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset.
  - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset.
  Don't use for:
  - General BigQuery querying or data analysis (use BigQuery-related tools instead).
  - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage.
  - Creating or modifying lineage links directly.

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](references/mcp-usage.md).

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:

1. **Executive Summary**: State the total number of downstream assets affected and the maximum depth of the impact. 2. **Critical Path**: Highlight high-priority downstream assets (e.g., assets containing "prod", "dashboard", "reporting", or "master" in their names). 3. **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 | 4. **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

1. **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. 2. **Strictly Banned Bypasses**:

  • Exclusively retrieve downstream relationships using the

`DataLineageServer:search_lineage` tool. 3. **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. 4. **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 Mar

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