How do I install the Bigquery AI Ml skill?

Run npx skillmds@latest add h3y6e/bigquery-ai-ml in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Bigquery AI Ml free to use?

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Who published Bigquery AI Ml?

h3y6e (@h3y6e) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Bigquery AI Ml by h3y6e — Agent Skill

Name: Bigquery AI Ml
Author: h3y6e

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 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.

h3y6e Updated Sep 17, 2026

File contents

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 - Multi-row semantic aggregation and summarization.
- AI.CLASSIFY: ai_classify.md - Classify text.
- AI.DETECT_ANOMALIES: ai_detect_anomalies.md - Detect anomalies.
- AI.EVALUATE: ai_evaluate.md - Evaluate models.
- AI.FORECAST: ai_forecast.md - Time-series forecasting.
- AI.GENERATE: ai_generate.md - Generate text using LLMs.
- AI.GENERATE_EMBEDDING: ai_generate_embedding.md - Generate embeddings.
- AI.GENERATE_TABLE: ai_generate_table.md - Table-valued AI generation.
- AI.IF: ai_if.md - Evaluate semantic conditions.
- AI.KEY_DRIVERS: ai_key_drivers.md - Identifies key drivers, this is a TVF.
- AI.SCORE: ai_score.md - Score data.
- AI.SEARCH: ai_search.md - Semantic search.
- AI.SIMILARITY: ai_similarity.md - Semantic similarity.
- Remote Models: remote_models.md - Working with remote models (Vertex AI).
- CONTRIBUTION_ANALYSIS: ml_contribution_analysis.md
  - Finds contributing factors, key drivers of change. Requires creating a MODEL entity.
- VECTOR_SEARCH: vector_search.md - Vector search best practices.

Related Skills

BigQuery Basics Skill: SKILL.md file for core BigQuery concepts, resource management, CLI, and client libraries.

---name: bigquery-ai-mldescription: 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 & MLBigQuery integrates with Vertex AI to provide powerful machine learning andgenerative AI capabilities directly within SQL queries using built-in functionslike `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.

Frequently asked questions