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/bigquery-ai-ml

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

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google-skills
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$ npx -y skills add google/skills --skill bigquery-ai-ml --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/bigquery-ai-ml

Context preview

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

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

SKILL.md

bigquery-ai-ml.SKILL.md
name: bigquery-ai-ml
metadata:
  category: AiAndMachineLearning
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,
  or leverage generative AI capabilities in BigQuery. Do not use for general
  BigQuery dataset, table, or job management requests.

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`.

Reference Directory

  • **Functions Reference**:
  • **AI.AGG**: [ai_agg.md](references/ai_agg.md) - Multi-row semantic

aggregation and summarization.

  • **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.

  • **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.

Read more
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