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bigquery-ai-ml

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics.

Skill by googleOfficial

IndexedApache-2.0★ 21,542
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/google-bigquery-ai-ml

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About

Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.

Use cases: backend, data, ml, writing

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/bigquery-ai-ml

What's inside

Skill name
bigquery-ai-ml
Description
Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, predict values, detect outliers or anomalies, find key drivers, perform semantic search or vector search, classify text, calculate similarity, summarize content, translate language, evaluate models, filter by semantic conditions, measure the causal effect of an intervention, compute correlations between columns, detect change points or structural breaks, extract trend or seasonality components, or leverage generative AI capabilities in BigQuery. Do not use for general BigQuery dataset, table, or job management requests.
License
Apache-2.0
Metadata
version: 1.1.1 · category: AiAndMachineLearning
Instructions
74 lines in SKILL.md · view on GitHub

Files (23)

  • SKILL.md
  • ai_agg.md · references/
  • ai_causal_effect.md · references/
  • ai_classify.md · references/
  • ai_detect_anomalies.md · references/
  • ai_evaluate.md · references/
  • ai_forecast.md · references/
  • ai_generate.md · references/
  • ai_generate_embedding.md · references/
  • ai_generate_table.md · references/
  • ai_if.md · references/
  • ai_key_drivers.md · references/
  • ai_score.md · references/
  • ai_search.md · references/
  • ai_similarity.md · references/
  • attribution.md · references/
  • ml_contribution_analysis.md · references/
  • ml_correlation.md · references/
  • ml_detect_change_points.md · references/
  • ml_seasonality.md · references/
  • ml_trend.md · references/
  • remote_models.md · references/
  • vector_search.md · references/

SKILL.md (first lines)

# BigQuery AI & ML

BigQuery integrates with Vertex AI to provide powerful machine learning and
generative AI capabilities directly within SQL queries using built-in functions
like `AI.FORECAST`, `AI.KEY_DRIVERS`, `AI.DETECT_ANOMALIES`, and `AI.GENERATE`.

## 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:bigquery-ai-ml)"`
and append `agent-skills/1.0 (skill:bigquery-ai-ml)` to `User-Agent` headers.

## Reference Directory

-   **Functions Reference**:

    -   **AI.AGG**: [ai_agg.md](references/ai_agg.md) - Multi-row semantic
        aggregation and summarization.
    -   **AI.CAUSAL_EFFECT**:
        [ai_causal_effect.md](references/ai_causal_effect.md) - Quantifies the
        impact of an intervention on a time series.
    -   **AI.CLASSIFY**: [ai_classify.md](references/ai_classify.md) - Classify
        text.
    -   **AI.DETECT_ANOMALIES**:
        [ai_detect_anomalies.md](references/ai_detect_anomalies.md) - Detect
        anomalies.
    -   **AI.EVALUATE**: [ai_evaluate.md](references/ai_evaluate.md) - Evaluate
        models.
    -   **AI.FORECAST**: [ai_forecast.md](references/ai_forecast.md) -
        Time-series forecasting.
    -   **AI.GENERATE**: [ai_generate.md](references/ai_generate.md) - Generate
        text using LLMs.
    -   **AI.GENERATE_EMBEDDING**:
        [ai_generate_embedding.md](references/ai_generate_embedding.md) -
        Generate embeddings.
    -   **AI.GENERATE_TABLE**:
        [ai_generate_table.md](references/ai_generate_table.md) - Table-valued
        AI generation.
    -   **AI.IF**: [ai_if.md](references/ai_if.md) - Evaluate semantic
        conditions.
    -   **AI.KEY_DRIVERS**: [ai_key_drivers.md](references/ai_key_drivers.md) -
        Identifies key drivers, this is a TVF.
    -   **AI.SCORE**: [ai_score.md](references/ai_score.md) - Score data.
    -   **AI.SEARCH**: [ai_search.md](references/ai_search.md) - Semantic
        search.
    -   **AI.SIMILARITY**: [ai_similarity.md](references/ai_similarity.md) -
        Semantic similarity.
    -   **Remote Models**: [remote_models.md](references/remote_models.md) -
        Working with remote models (Vertex AI).
    -   **CONTRIBUTION_ANALYSIS**:
        [ml_contribution_analysis.md](references/ml_contribution_analysis.md)
        -   Finds contributing factors, key drivers of change. Requires creating
            a MODEL entity.
    -   **ML.CORRELATION**: [ml_correlation.md](references/ml_correlation.md) -
        Calculates correlation between columns, optionally sliced by dimensions.
    -   **ML.DETECT_CHANGE_POINTS**:
        [ml_detect_change_points.md](references/ml_detect_change_points.md) -
        Detects structural breaks or sustained shifts in a time series.
    -   **ML.SEASONALITY**: [ml_seasonality.md](references/ml_seasonality.md) -
        Extracts seasonal components from a time series.
    -   **ML.TREND**: [ml_trend.md](references/ml_trend.md) - Extracts the
        long-term trend component from a time series.
    -   **VECTOR_SEARCH**: [vector_search.md](references/vector_search.md) -
        Vector search best practices.

## Related Skills

-   [BigQuery Basics Skill](../bigquery-basics): SKILL.md file for core BigQuery
    concepts, resource management, CLI, and client libraries.

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    Last commit (this folder)
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    From GitHub (fetched Oct 24, 2026).

    Details

    Version
    1.1.1
    License
    Apache-2.0
    First seen
    Oct 24, 2026
    Last checked
    Oct 24, 2026

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    Cite this page

    bigquery-ai-ml skill. Agent Mart. https://agentmart.dev/skills/google-bigquery-ai-ml (last updated 2026-10-24)