Skip to main content
skill Claude Code Gemini CLI CX Codex official · Google

datalineage-bigquery-asset-impact-analysis — Claude Code skill

Maps downstream BigQuery dependencies before you change, delete, or pause an asset. Use it to assess the blast radius of a broken or stale table or view.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add google/skills --skill datalineage-bigquery-asset-impact-analysis -a claude-code
Open on GitHub

What datalineage-bigquery-asset-impact-analysis does

This skill maps downstream dependencies for a BigQuery table or view through the Data Lineage MCP Server. It finds affected tables, dashboards, and processes, separates direct impact from cascading impact, then returns a complete blast radius table.

The agent checks an FQN such as bigquery:{project_id}.{dataset_id}.{table_or_view_id}, obtains the dataset location with bq show --format=json {project_id}:{dataset_id}, and calls DataLineageServer:search_lineage with DOWNSTREAM. Its default search depth is 10, with up to 5 processes per link.

You need access to the Data Lineage API on Google Cloud and an active client connection to the Data Lineage MCP Server. Install this before changing or pausing a BigQuery asset; it is the wrong fit for general BigQuery analysis or assets outside BigQuery lineage.

What it helps with

  • find tables that depend on a BigQuery source
  • assess the impact of deleting a table or view
  • spot dashboards with cascading stale data
  • trace ETL processes between dependent assets
  • check impact before pausing updates

Example prompts for the agent

  • Check the blast radius for `bigquery:my-prod-project.analytics.orders`.
  • Which downstream tables and dashboards would a change to this BigQuery view affect?
  • Find dependencies and processes for `bigquery:my-prod-project.analytics.orders`.

How to install datalineage-bigquery-asset-impact-analysis

1Skills CLI (Vercel)

npx skills add google/skills --skill datalineage-bigquery-asset-impact-analysis -a claude-code

2Manually: put the files in place

~/.claude/skills/datalineage-bigquery-asset-impact-analysis/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/datalineage-bigquery-asset-impact-analysis/

From the same set172

The whole set →
bigquery-basics official google Manages BigQuery resources and runs SQL queries. Use it to create datasets, tables and views, or handle basic data ingestion and analysis. Claude Code Gemini CLI CX Codex 17,678installs cloud-run-basics official google This skill helps an agent manage Cloud Run services, jobs, and worker pools when a project needs HTTP deployment, scheduled work, or pull-based background processing. Claude Code Gemini CLI CX Codex 17,532installs gemini-api official google Connects Gemini API from Google Cloud Agent Platform to the agent. Gives access to Gemini models, multimodal input, function calling, and context caching. Claude Code Gemini CLI CX Codex 17,116installs google-cloud-recipe-auth official Google LLC This skill explains Google Cloud authentication and permissions. Use it when setting up IAM, ADC, or service accounts for local code and production workloads. Claude Code Gemini CLI CX Codex 15,450installs google-cloud-recipe-onboarding official Google LLC Guides a developer through a first Google Cloud project: CLI checks, sign-in, project setup and billing. It fits a personal first project. Claude Code Gemini CLI CX Codex 15,390installs cloud-sql-basics official google This skill helps create and explain Cloud SQL resources for MySQL, PostgreSQL, and SQL Server. Use it when setting up a database in Google Cloud. Claude Code Gemini CLI CX Codex 14,679installs google-cloud-waf-security official google This skill reviews Google Cloud workloads against the security pillar of the Well-Architected Framework and suggests actions for IAM, networks, data, and operations. Claude Code Gemini CLI CX Codex 14,620installs google-cloud-waf-cost-optimization official google Reviews Google Cloud workloads through the Well-Architected Cost Optimization pillar. Use it to inspect spending, resize resources, assess discounts, or find idle capacity. Claude Code Gemini CLI CX Codex 14,266installs

Similar

Questions about datalineage-bigquery-asset-impact-analysis

How do I install datalineage-bigquery-asset-impact-analysis in Claude Code?

Run npx skills add google/skills --skill datalineage-bigquery-asset-impact-analysis -a claude-code. The skill is placed at ~/.claude/skills/datalineage-bigquery-asset-impact-analysis/SKILL.md.

What does datalineage-bigquery-asset-impact-analysis do?

It analyzes downstream lineage for a BigQuery table or view and reports the assets, processes, and dashboards affected by a failure, change, or paused update.

What does this skill need to work?

It requires access to the Data Lineage API on Google Cloud and an active client connection to the Data Lineage MCP Server. The agent also needs the correct BigQuery asset FQN.

Source text

SKILL.md · Apache-2.0
---
name: datalineage-bigquery-asset-impact-analysis
metadata:
  version: "1.0.2"
  category: BigDataAndAnalytics
description: >-
  Analyzes the downstream impact (blast radius) using data lineage on Google Cloud 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 **data lineage (Knowledge Catalog) MCP Server** on
Google Cloud to discover relationships between assets.

## Attribution

**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you
MUST read [Usage Attribution](references/attribution.md). For commands executed
directly in the terminal (never in generated scripts, Terraform, or user code),
prefix `gcloud` with
`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:datalineage-bigquery-asset-impact-analysis)"`
and append `agent-skills/1.0 (skill:datalineage-bigquery-asset-impact-analysis)` to `User-Agent` headers.

## Prerequisites

This skill requires access to the data lineage API on Google Cloud 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
        Markdown file or artifact containing the details unless you have
        explicitly executed file-writing tools to create it.

## Reference Directory

-   [MCP Usage](references/mcp-usage.md): Using the data lineage remote MCP
    server on Google Cloud and tool preferences.

## External Documentation

-   [Knowledge Catalog Data Lineage Documentation](https://cloud.google.com/dataplex/docs/about-data-lineage)
-   [Use the Data Lineage MCP server](https://docs.cloud.google.com/dataplex/docs/use-lineage-mcp)
-   [Knowledge Catalog Data Lineage API Reference](https://cloud.google.com/dataplex/docs/reference/data-lineage/rest)

© google · Apache-2.0 · google/skills

See also

Project sponsors

Companies that keep this analytics open
Gold sponsor

Impressions, clicks and code copies — open statistics. We keep the numbers public for the same reason NeBlask itself is public. Become a sponsor